KR102458663B1 - System and method for providing to-do-list of user - Google Patents

Abstract

A system and method are provided for providing a user's to-do list. A device for providing a user's to-do list, wherein at least one task to be performed by the user in the to-do list is determined based on data obtained by a communication unit communicating with an external device, a display, and an application executed on the display Determining at least one keyword used for the purpose of displaying a GUI for selecting at least one of the at least one keyword in the keyword list by determining at least one keyword, generating a keyword list for the determined at least one keyword, and controlling the display includes a processor.
In this case, the device may determine at least one task to be performed by the user using a rule-based or artificial intelligence algorithm. When determining at least one task using an artificial intelligence algorithm, the device may use a machine learning, neural network, or deep learning algorithm.

Description

SYSTEM AND METHOD FOR PROVIDING TO-DO-LIST OF USER

The present invention relates to a system and method for providing a user's to-do list.

In addition, the present disclosure relates to an artificial intelligence (AI) system for simulating functions such as cognition and judgment of the human brain by using a machine learning algorithm such as deep learning and an application technology thereof.

As multimedia technology and network technology develop, a user can use a desired service through various devices and service providing servers. In addition, users can communicate with other users' devices using their own devices. As users are able to use various devices and service providing servers, it is difficult for users to effectively check what they need to do. Accordingly, there is a demand for a technique for generating and providing a user's to-do list by analyzing the user's device-related operation.

In addition, artificial intelligence systems have recently been introduced into the image processing field.

An artificial intelligence system is a computer system that implements human-level intelligence, and unlike the existing rule-based smart system, the machine learns, judges, and becomes smarter by itself. The more the AI system is used, the better the recognition rate and the more accurate understanding of user preferences, and the existing rule-based smart systems are gradually being replaced by deep learning-based AI systems.

Artificial intelligence technology consists of machine learning (deep learning) and element technologies using machine learning.

Machine learning is an algorithm technology that categorizes/learns the characteristics of input data by itself, and element technology uses machine learning algorithms such as deep learning to simulate functions such as cognition and judgment of the human brain. It consists of technical fields such as understanding, reasoning/prediction, knowledge expression, and motion control.

The various fields where artificial intelligence technology is applied are as follows. Linguistic understanding is a technology for recognizing and applying/processing human language/text, and includes natural language processing, machine translation, dialogue system, question and answer, and speech recognition/synthesis. Visual understanding is a technology that recognizes and processes objects as if they were human eyes, and includes object recognition, object tracking, image search, human recognition, scene understanding, spatial understanding, image improvement, and the like. Inferential prediction is a technology for logically reasoning and predicting by judging information, and includes knowledge/probability-based reasoning, optimization prediction, preference-based planning, and recommendation. Knowledge expression is a technology that automatically processes human experience information into knowledge data, and includes knowledge construction (data generation/classification) and knowledge management (data utilization). Motion control is a technology for controlling autonomous driving of a vehicle and movement of a robot, and includes motion control (navigation, collision, driving), manipulation control (action control), and the like.

1. Unexamined Patent Publication No. 10-2016-0063913 (2016. 06. 07.) 2. Laid-open Patent Publication No. 10-2014-0136820 (2014. 12. 01.)

A system and method for providing a user's to-do list for determining a task in the user's to-do list based on the user's device and the operation of a service providing server to which the user is subscribed may be provided.

Also, it is possible to provide a device and method for providing a user's to-do list by editing a keyword used to determine a task in the to-do list, and displaying a candidate task list and a GUI for editing the task list.

In addition, a system and method for providing a user's to-do list, providing a task for replacing a task in the to-do list, may be provided.

Also, it is possible to provide a system and method for providing a user's to-do list capable of determining whether a task in the to-do list has been performed based on condition information for determining whether a task in the to-do list has been performed.

According to one side, in a device for providing a user's to-do list (To Do List), the communication unit for communicating with an external device; display; and determining at least one keyword used to determine at least one task to be performed by the user in the to-do list, based on data obtained by the application executed on the display, for the determined at least one keyword and a processor for generating a keyword list and displaying a GUI for selecting at least one of the at least one keyword in the keyword list by controlling the display.

According to another aspect, there is provided a method for providing a user's to-do list by a device, comprising: acquiring data used to generate the to-do list from an application executed on a display of the device; determining, based on the obtained data, at least one keyword used to determine at least one task to be performed by the user in the to-do list; generating a keyword list for the determined at least one keyword; and displaying a GUI for selecting at least one of the at least one keyword in the keyword list by controlling the display.

According to another side, in the server that provides the user's to-do list,

a communication unit for receiving data obtained by an application executed on the device from the user's device; a memory for storing the received data and data related to the service subscribed by the user; and determining at least one keyword used to determine at least one task to be performed by the user in the to-do list based on the received data, and based on the received data and data related to a service to which the user has subscribed. to determine at least one candidate task related to the at least one keyword, wherein the communication unit may transmit the determined at least one candidate task to the user's device.

According to one side, a method for a server to provide a user's to-do list, the method comprising: receiving data obtained by an application executed on the device from the user's device; determining at least one keyword used to determine at least one task to be performed by the user in the to-do list based on the received data; determining at least one candidate task related to the at least one keyword based on the received data and data related to the service subscribed by the user stored in the server; and transmitting the determined at least one candidate task to the user's device.

According to another aspect, it is possible to provide a computer-readable recording medium in which the device records a program for executing a method of providing a user's to-do list in a computer.

BRIEF DESCRIPTION OF THE DRAWINGS The present invention can be easily understood by the following detailed description and combination of the accompanying drawings, in which reference numerals mean structural elements.
1 is a diagram illustrating an example in which a device provides a to-do list for a task to be performed by a user, according to an embodiment.
2 is a flowchart of a method for a device to manage a user's to-do list according to an exemplary embodiment.
3 is a flowchart of a method for generating, by a device, a keyword list used to determine a task to be performed by a user and selecting a keyword, according to an exemplary embodiment.
4 is a diagram illustrating an example in which a device displays a keyword list on an execution screen of a message application, according to an embodiment.
5 is a diagram illustrating an example in which a device displays a keyword list on an execution screen of a call application, according to an embodiment.
6 is a diagram illustrating an example in which a device edits a keyword list according to a user input to a GUI, according to an embodiment.
7 is a diagram illustrating an example in which a device displays a keyword list on an execution screen of an application being executed on a display based on data obtained from a plurality of applications, according to an embodiment.
8 is a flowchart of a method for a device to generate a candidate task list according to an embodiment.
9 is a diagram illustrating an example in which a device displays a list of candidate tasks, according to an embodiment.
10 is a diagram illustrating an example in which a device displays a list of candidate tasks, according to another embodiment.
11 is a flowchart of a method for a device to generate a to-do list according to an exemplary embodiment.
12 is a diagram illustrating an example in which a device displays a to-do list, according to an embodiment.
13 is a diagram illustrating an example in which a device displays a to-do list, according to another embodiment.
14 is a diagram illustrating an example in which a device provides additional information related to a task in a to-do list, according to an embodiment.
15 is a flowchart of a method for a device to provide a task to replace a previously determined task according to an exemplary embodiment.
16 is a diagram illustrating an example in which a device provides a candidate task for a sub-task by identifying a user's intention and provides an additional task for the determined task, according to an embodiment.
17 is a diagram illustrating an example in which a device provides an alternative task to replace a sub task, according to an embodiment.
18 is a flowchart of a method of monitoring, by a device, whether a task in a to-do list is performed, according to an exemplary embodiment.
19 is a diagram for describing a process of monitoring whether a device has performed a task in a to-do list, according to an embodiment.
20 is a diagram for describing a process of monitoring whether a device has performed a task in a to-do list, according to another exemplary embodiment.
21 is a diagram for describing a process of monitoring whether a device has performed a task in a to-do list, according to another exemplary embodiment.
22 is a flowchart of a method in which a server determines a candidate task, a device generates a to-do list, and monitors whether a task in the to-do list is performed, according to an embodiment.
23 is a flowchart of a method for a device to generate a to-do list, a server to determine a candidate task for determining a task in the to-do list, and to monitor whether a task in the to-do list is performed, according to another exemplary embodiment.
24 and 25 are block diagrams of a device according to an exemplary embodiment.
26 is a block diagram of a server according to an embodiment.
27 is a block diagram of a processor according to an embodiment.
28 is a block diagram of a data learning unit according to an exemplary embodiment.
29 is a block diagram of a data recognition unit according to an exemplary embodiment.
30 is a diagram illustrating an example of learning and recognizing data by interworking between a device and a server according to an embodiment.
31 is a flowchart of a method for managing a user's to-do list by a first processor and a second processor according to an exemplary embodiment.
32 is a flowchart of a method for managing a user's to-do list by a first processor, a second processor, and a third processor according to an exemplary embodiment.
33 is a flowchart illustrating a situation in which a device manages a to-do list using a plurality of servers according to an embodiment.
34 is a flowchart illustrating a situation in which a device manages a to-do list using a first processor, a second processor, and a server according to an embodiment.

The terms used in the present invention have been selected as currently widely used general terms as possible while considering the functions in the present invention, but these may vary depending on the intention or precedent of a person skilled in the art, the emergence of new technology, and the like. In addition, in a specific case, there is a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the corresponding invention. Therefore, the term used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, rather than the name of a simple term.

In the entire specification, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated. Also, as used herein, the term “unit” refers to a hardware component such as software, FPGA, or ASIC, and “unit” performs certain roles. However, 'part' is not limited to software or hardware. The 'unit' may be configured to reside on an addressable storage medium or it may be configured to refresh one or more processors. Thus, by way of example, “part” refers to components such as software components, object-oriented software components, class components, and task components, processes, functions, properties, procedures, subroutines, segments of program code, drivers, firmware, microcode, circuitry, data, databases, data structures, tables, arrays and variables. The functionality provided within components and “parts” may be combined into a smaller number of components and “parts” or further divided into additional components and “parts”.

Terms such as first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component. and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

1 is a diagram illustrating an example in which a device 1000 provides a to-do list for a task to be performed by a user, according to an exemplary embodiment.

Referring to FIG. 1 , a device 1000 may obtain data used to generate a user's to-do list from a plurality of applications installed in the device 1000 . Here, the plurality of applications includes a call application 101 for transmitting and receiving voice signals between the user's device 1000 and another user's device, a message application 102 for communication between the user's device 1000 and another user's device, It may include, but is not limited to, a user's e-mail application 103, a memo pad application 104 for recording a user's memo, or a schedule management application (not shown) for managing a user's schedule.

The device 1000 may analyze data obtained from an application executed and/or installed in the device 1000 , determine at least one task to be performed by the user, and generate a to-do list for the at least one task. The device 1000 may notify the user of the created to-do list. The device 1000 may display a to-do list on the display of the device 1000 .

Also, the device 1000 may monitor whether at least one task in the to-do list is performed. The device 1000 may update the task in the to-do list based on the monitoring result.

The device 1000 includes a smart phone, a tablet PC, a PC, a smart TV, a mobile phone, a personal digital assistant (PDA), a laptop, a media player, a micro server, a global positioning system (GPS) device, an e-book terminal, a digital broadcasting terminal, and a navigation device. , kiosks, MP3 players, digital cameras, and other mobile or non-mobile computing devices. Also, the device 1000 may be a wearable device such as a watch, glasses, a hair band, and a ring having a communication function and a data processing function.

2 is a flowchart of a method for the device 1000 to manage a user's to-do list according to an exemplary embodiment.

In operation S210 , the device 1000 may generate a to-do list of the user. The device 1000 may analyze data obtained from an application executed and/or installed in the device 1000 , determine at least one task to be performed by the user, and generate a to-do list for the at least one task.

Also, the device 1000 may receive data related to data acquired by an application in the device 1000 from the server 2000 . Here, the server 2000 may be a service providing server to which a user is subscribed, but is not limited thereto. The device 1000 may determine candidate tasks for at least one task to be performed by the user by combining all or part of the data obtained from the server 2000 and the data obtained by an application in the device 1000 . The device 1000 may determine at least one selected from the candidate tasks as a task to be performed by the user, and may generate a to-do list.

In operation S220 , the device 1000 may monitor whether at least one task in the to-do list is performed. The device 1000 may obtain condition information used to determine whether at least one task in the to-do list has been performed, and monitor whether at least one task in the to-do list is performed based on the condition information. Here, the condition information may include, but is not limited to, an application used to perform a predetermined task, user operation information related to the application, detailed operation information of the application according to the user's operation information, and the like.

In step S230 , the device 1000 may update the to-do list based on the monitoring result. For example, if it is determined that the first task in the to-do list has been performed, the device 1000 may delete the first task from the to-do list. Also, when it is determined that the first task in the to-do list has not been performed by a predetermined time, the device 1000 may output information indicating that the first task has not been performed.

3 is a flowchart of a method for generating a keyword list and selecting keywords used by the device 1000 to determine a task to be performed by a user, according to an exemplary embodiment.

In operation S310 , the device 1000 may obtain data used to generate the user's to-do list from an application executed on the display of the device 1000 . For example, the device 1000 may acquire data about a message transmitted and received by a chatting application executed on the display.

Also, the device 1000 may obtain data used to generate the user's to-do list from a plurality of applications installed in the device 1000 . The acquired data includes call contents through the device 1000 , messages transmitted and received through the device 1000 (eg, short message service (SMS), multi-media message service (MMS), chat messages, E-Mail, etc.) ), voice contents recorded in the device 1000 and text files stored in the device 1000, photos, videos, user schedule contents, memos, etc. may be data, but is not limited thereto.

In operation S320 , the device 1000 may determine a keyword used to determine a task to be performed by the user based on the obtained data. For example, when the application executed on the display is a chatting application for communication between the user's device 1000 and another user's external device, the device 1000 receives the at least One keyword can be extracted. Specifically, the device 1000 may analyze text transmitted/received between the device 1000 and an external device, and may determine a keyword used to determine a task to be performed by the user based on the analysis result.

In relation to the method of analyzing the text and the method of determining the keyword, the device 1000 may perform the analysis using various data mining techniques. Also, the device 1000 may analyze contents of text transmitted/received between the device 1000 and an external device by using various natural language interpretation techniques. In this case, the device 1000 may interpret the meaning of the text content through a natural language processing method such as morpheme analysis and syntax analysis. The device 1000 may determine keywords corresponding to interrogative words such as “who”, “when”, “where”, “what”, “how”, and “why” based on the meaning of the content of the interpreted text. have.

For another example, if the application executed on the display is a call application through the device 1000 , the device 1000 converts a call voice into text using STT (Speech To Text) conversion technology in real time, and converts the text The analysis can determine the keywords used to determine the task. Also, when a call application is executed and a call is connected between the device 1000 and an external device, the device 1000 may record a call voice. The device 1000 may convert the recorded voice call into text, and may determine a keyword by analyzing the converted text. Also, the device 1000 may transmit a recorded voice call to the server 2000 and receive text converted from the voice call from the server 2000 .

As another example, when the application executed on the display is a gallery application for managing photos or videos, the device 1000 processes the photos or videos stored in the device 1000 to determine a task from the photos or videos. You can decide which keywords to use.

In addition, the device 1000 determines a keyword used to determine a task to be performed by the user based on data acquired by an application executed on the display and data acquired by at least one application installed in the device 1000 . can

In operation S330 , the device 1000 may generate a keyword list for keywords. The device 1000 may generate a keyword list including all keywords generated from data acquired by an application executed on the display. Also, the device 1000 may combine all or some of the generated keywords to generate a keyword list used to determine at least one task to be performed by the user in the to-do list.

In addition, the device 1000 generates a keyword list by combining all or part of a keyword generated from data acquired by an application executed on the display and a keyword generated from data acquired by an application installed on the device 1000 . can do. Here, when the device 1000 generates a keyword list using not only keywords generated from data acquired by an application running on the display, but also keywords generated from data acquired by other applications installed on the device 1000, It is possible to create a list of keywords that more closely match the user's intention.

In operation S340 , the device 1000 may display a graphic user interface (GUI) for selecting at least one of keywords in the keyword list. Here, the GUI may receive a predetermined command or data input from the user. The processor of the device 1000 may generate the GUI and output the GUI on the display screen by controlling the display.

Also, the device 1000 may display a GUI for selecting at least one of the keywords in the keyword list by controlling the display to be superimposed on the execution screen of the executed application. In this case, the device 1000 may display the GUI at a predetermined location on the execution screen of the executed application. Also, the device 1000 may display the GUI based on the location of the area where information is not displayed on the execution screen of the executed application. Also, the device 1000 may display the GUI semi-transparently on the execution screen of the application.

Also, the device 1000 may display the GUI on a new execution screen of the application, not on the execution screen of the previously executed application. For example, the new execution screen may be an execution screen displaying only a GUI for selecting at least one of keywords in the keyword list.

4 is a diagram illustrating an example in which the device 1000 displays a keyword list 810 on an execution screen 801 of a message application, according to an embodiment.

A user may transmit/receive a message to/from another user through a message application installed in the device 1000 . The device 1000 may obtain data on text exchanged between users from the message application. The device 1000 may analyze the content of a conversation between the user of the device 1000 and the user of the external device based on the acquired data. The device 1000 may determine at least one keyword 820 used to determine a task to be performed by the user based on the analyzed subject and contents. The device 1000 may generate a keyword list 810 for the determined keyword 820 and display it overlaid on the execution screen 801 of the message application.

Referring to FIG. 4 , the device 1000 may display a message transmitted and received by the user (B) of the device 1000 and the user (Susan) of the external device through the message application on the execution screen 801 of the message application. . For example, the device 1000 transmits/receives between the user (me) of the device 1000 and the user (Susan) of the external device through the message application, "Don't forget to buy a souvenir in Japan during your vacation", "Yes, a gift" I'll buy it", "Have you booked your plane ticket?" and "No, not yet.." is obtained, and based on the obtained message, it can be interpreted that the user should reserve a plane ticket to Japan during vacation and buy a present for Susan. Accordingly, the device 1000 may determine “Japan”, “gift”, “vacation”, “airplane”, and “reservation” as the keywords 820 based on the analysis. The device 1000 generates the determined keywords 820, “Japan,” “gift,” “vacation,” “airplane,” and “reservation,” as the keyword list 810, and displays it on the execution screen 801 of the message application. can do. In this case, the device 1000 may display a GUI for selecting at least one of the at least one keyword 820 in the keyword list 810 . An operation of selecting and editing at least one keyword 820 in the keyword list 810 through the GUI will be described with reference to FIG. 6 .

5 is a diagram illustrating an example in which the device 1000 displays a keyword list 810 on the execution screen 802 of a call application, according to an embodiment.

Referring to FIG. 5 , for example, the device 1000 performs a call between the user (me) of the device 1000 and the user (Susan) of the external device through a call application saying, "You go to Japan during vacation? Buying my gift? Don't forget", "Yes, I'll buy you a present", "Did you book your plane ticket?" and "No, not yet..." call voices can be recorded. The device 1000 may convert the recorded voice call into text, and based on the changed text, the device 1000 may interpret that the user should reserve a plane ticket to Japan during vacation and buy a present for Susan. Accordingly, the device 1000 may determine “Japan”, “gift”, “vacation”, “airplane”, and “reservation” as the keywords 820 based on the analysis. The device 1000 may generate the keyword 820 as a keyword list 810 and display it on the execution screen 802 of the call application.

6 is a diagram illustrating an example in which the device 1000 edits a keyword list according to a user input to a GUI, according to an embodiment.

Referring to FIG. 6 , the device 1000 displays a GUI for selecting at least one of the keyword lists including “Japan”, “gift”, “vacation”, “airplane”, and “reservation” as keywords on the execution screen of the message application. (801) can be displayed superimposed. For example, the device 1000 may display “+” and “-” 831 at the top of the keyword list.

The device 1000 may receive an input of selecting “-” and an input of deleting “vacation” 821 from the keyword list through the GUI. Here, an input for selecting “-” may be a touch signal, and an input for deleting “vacation” 821 may be a drag-and-drop signal, but is not limited thereto. Drag means a touch gesture that moves a touch point from one location to another. It may include various gestures. The device 1000 deletes “vacation” from the keyword list from the keyword list by controlling the display, and displays a keyword list composed of keywords “Japan”, “gift”, “airplane”, and “reservation” on the execution screen of the display can do.

Also, the device 1000 may receive an input for selecting “+” through the GUI. In this case, the device 1000 may display a keyboard interface on the execution screen of the display to input or modify a keyword. The user may additionally insert "accommodation" and "passport photo" 822 into the keyword list through the keyboard interface. The device 1000 may display a keyword list including keywords “Japan”, “gift”, “airplane”, “reservation”, “accommodation”, and “passport photo” on the execution screen of the display.

7 is a diagram illustrating an example in which the device 1000 displays a keyword list on an execution screen of an application being executed on a display based on data obtained from a plurality of applications, according to an embodiment.

As described in FIG. 4 , the device 1000 may display a message transmitted/received between the user (B) and the other user (Susan) on the execution screen 801 of the message application by executing the message application. Based on the message obtained by the message application, the device 1000 may interpret the message as “the user should reserve a plane ticket to Japan during vacation and buy a present for Susan”. Accordingly, the device 1000 may determine “Japan”, “gift”, “vacation”, “airplane”, and “reservation” as keywords based on the above analysis.

Here, before generating the keyword list using the determined keyword, the device 1000 may acquire data related to the first item in the keyword list from another application installed in the device 1000 . Here, the item may mean a material that can be commonly applied among at least one keyword in the keyword list. The device 1000 may additionally generate a keyword related to the first item based on data obtained from another application. For example, the device 1000 determines an item for the keywords of “Japan”, “gift”, “vacation”, “airplane”, and “reservation” as “travel”, and data related to “travel” is stored in the device ( 1000) can be checked. The device 1000 may additionally generate a keyword related to “travel” based on data related to “travel” stored in the device 1000 . The device 1000 may obtain the text “I will submit a vacation plan one month before going on vacation” from the memo application 803 , and generate “vacation plan” 823 as an additional keyword. The device 1000 may generate “Japan”, “gift”, “vacation”, “airplane”, “reservation”, and “vacation plan” 823 as a keyword list and display it on the execution screen of the display.

8 is a flowchart of a method for generating a candidate task list by the device 1000 according to an exemplary embodiment.

In operation S410 , the device 1000 may receive an input for selecting a first keyword related to the first item from the keyword list through the GUI. Here, the item may mean a material that can be commonly applied among at least one keyword in the keyword list. For example, "airplane", "accommodation", "rental car", "reservation", "airline site", etc. may be included in the keyword list. The device 1000 may determine a keyword item of "airplane", "reservation", and "airline site" as "airplane reservation". The device 1000 may receive a touch signal through which the user selects a first keyword related to the first item on the screen of the display.

Also, the device 1000 may receive an input for correcting, adding, or deleting a keyword in the keyword list through the GUI. For example, the device 1000 may receive an input signal for deleting a second keyword that is not related to the first item in the keyword list. Here, the input signal may be a touch signal or a drag-and-drop signal. As another example, the device 1000 may display an icon on the execution screen of the display so that the user can directly input or modify a keyword in the keyword list. When the user touches the icon, the device 1000 may display the keyboard interface on the execution screen of the display so that the user can directly input or modify a keyword related to the first item. The device 1000 may receive a keyword used to determine a task through the keyboard interface.

In operation S420 , the device 1000 may determine at least one candidate task for the first item based on the selected first keyword. The device 1000 combines all or part of the selected first keyword, data related to the first keyword acquired by at least one application installed in the device 1000 , and data related to the first keyword acquired from the server 2000 . Thus, at least one candidate task may be determined. Here, the server 2000 may be a service providing server to which a user is subscribed, but is not limited thereto. Here, the at least one candidate task may be provided in the form of a sentence generated by combining all or a part of data related to the first keyword.

Also, when there are a plurality of selected keywords, the device 1000 may determine at least one candidate task by classifying the plurality of keywords for each category and combining all or some of the keywords within the same category.

In operation S430 , the device 1000 may display a list of candidate tasks for the determined at least one candidate task. The device 1000 may classify the plurality of determined candidate tasks by category for each item, and group candidate tasks belonging to the same category to generate a candidate task list for each group.

Also, the device 1000 may classify a plurality of determined candidate tasks according to a user's schedule, group candidate tasks belonging to the same schedule, and generate a candidate task list for each group. The device 1000 may display the generated candidate task list.

9 is a diagram illustrating an example in which the device 1000 displays a candidate task list 910, according to an embodiment.

The device 1000 includes all or part of the first keyword selected by the user, data related to the first keyword acquired by a plurality of applications installed in the device 1000 , and data related to the first keyword acquired from the server 2000 . can be combined to determine the candidate task 920 for the first item. Here, the server 2000 may be a service providing server to which a user is subscribed, but is not limited thereto.

As described in FIG. 7 , the device 1000 includes keywords “Japan”, “gift”, “vacation”, “airplane”, “reservation” and “vacation plan” selected by the user, a plurality of installed in the device 1000 . By using data related to the selected keyword from the application of , and data related to the keyword from the server 2000, an item is determined as “Japan travel”, “Japan travel” related to “Japan travel”, and “booking an airplane ticket” ", "Book accommodation A", "book accommodation B", "take passport photo", "submit vacation plan" and "buy Susan gift" may be determined as candidate tasks 920 .

The device 1000 may display the candidate task list 910 for the candidate task 920 . In this case, the device 1000 may overlap and display the screen displaying the candidate task list 910 on the execution screen of the application, or may display it as a separate execution screen. Also, the device 1000 may display a GUI 911 for editing the candidate task list 910 . For example, the device 1000 may display a GUI 911 for re-recommending, confirming, and editing the candidate task 920 .

10 is a diagram illustrating an example in which the device 1000 displays a candidate task list 910 according to another embodiment.

The device 1000 may acquire additional keywords from the service providing server 2000 to which the user is subscribed as well as the keyword selected by the user. Here, the additional keyword is a keyword related to the item for the selected keyword. As described in FIG. 9 , when the keyword is “Japan”, “gift”, “vacation”, “airplane”, “reservation”, and “vacation plan”, the device 1000 selects an item for the keyword “travel in Japan” ", and "Japanese attractions" and "Japanese restaurants" related to "travel in Japan" may be determined as additional keywords.

The device 1000 may determine a candidate task related to the item based on the additional keyword. The device 1000 may determine, as candidate tasks, to go to an XX festival and to a go to an OO restaurant in relation to the “Japanese attraction” based on “Japanese spots” and “Japanese restaurants”.

The device 1000 may distinguish the candidate task determined based on the additional keyword obtained from the service providing server 2000 from the candidate task determined based on the keyword selected by the user and display it on the execution screen of the display. For example, as shown in FIG. 10 , the device 1000 displays ( 920 ) a candidate task determined based on a keyword selected by the user at the top of the execution screen, and the addition obtained from the service providing server 2000 . Candidate tasks determined based on the keyword may be displayed 930 at the bottom of the execution screen.

Also, when the device 1000 receives an input (eg, a touch signal) for selecting a candidate task in the candidate task list 910 through the execution screen of the display, the device 1000 displays information related to the selected candidate task. can provide For example, when the device 1000 receives an input selecting “go to the XX festival”, the device 1000 may display “how to go to the XX festival”, “the period during which the XX festival is held”, “how to reserve the XX festival” and You can provide "link information related to the XX festival", etc. In this case, the device 1000 may receive information related to “going to the XX festival” from the service providing server 2000 to which the user is subscribed.

11 is a flowchart of a method for a device to generate a to-do list according to an exemplary embodiment.

In operation S510 , the device 1000 may display a candidate task list and a GUI for editing the candidate task list.

In operation S520 , the device 1000 may receive a user input through a GUI for editing the candidate task list, and generate a to-do list based on the user input. The device 1000 may generate a to-do list including at least one main task and at least one sub-task dependent on the main task, based on the candidate task list and the user input. Also, the device 1000 may determine tasks to be performed by the user in the candidate task list based on the candidate task list and the user input. The device 1000 may determine a task for an upper element from among the determined tasks as a main task, and may determine a task for a lower element corresponding to the upper element as a sub task.

For example, if the item for the candidate task list is related to "travel in Japan", the candidate task list is "book a flight ticket", "book a hotel", "search a destination", "book a flight ticket for airline A" , "booking airline tickets for airline B", "setting travel dates", "rental car rental", "connecting to accommodation comparison sites", "visiting attractions C", "visiting local restaurants in E", etc. In this case, the device 1000 determines “reserving a plane ticket” as the first main task, and performs “booking a plane ticket for airline A”, “booking a plane ticket for airline B”, and “setting a travel date” as the first main task. It can be determined as a sub-task for a task. Also, the device 1000 may determine “booking accommodation” as the second main task, and determine “connecting to an accommodation comparison site” as a sub-task for the second main task. In addition, the device 1000 may determine "Searching for a travel destination" as the third main task, and determine "Visit C spot C" and "Explore a restaurant in area E" as sub-tasks for the third main task. Also, the device 1000 may determine “rental car rental” as one main task, and may determine it as a sub-task for the first to third main tasks.

In operation S530, the device 1000 may display the created to-do list. Also, the device 1000 may output notification information regarding the performance of the first task when the first task in the to-do list is to be performed. The device 1000 may superimpose the notification information on the execution screen of the display or output the notification information as a voice signal.

12 is a diagram illustrating an example in which the device 1000 displays a to-do list, according to an embodiment.

As shown in FIG. 10 , the user selects "Travel to Japan", "Reserve a plane ticket", "Reserve accommodation B", "Take a passport photo", "Submit a vacation plan", and "Buy Susan gift" from the list of candidate tasks. " and "Go to XX Festival" can be selected as tasks. In this case, the device 1000 may receive a touch signal for selecting a task from the candidate task list through the GUI on the execution screen of the display.

Referring to FIG. 12 , the device 1000 may configure the task selected by the user as a to-do list, and display the to-do list on the execution screen of the display ( 960 ). For example, the device 1000 may display 960 a to-do list related to “Travel to Japan” 950 on the execution screen of the display. Also, the device 1000 may display a GUI providing a function for editing tasks in the to-do list on the execution screen of the display.

13 is a diagram illustrating an example in which the device 1000 displays a to-do list, according to another embodiment.

Referring to FIG. 13 , tasks in the user's to-do list include "Travel to Japan", "Reserve a plane ticket", "Reserve accommodation B", "Take a passport photo", "Submit a vacation plan", "Buy Susan gift" And when it is determined to “go to the XX festival”, the device 1000 may classify tasks in the to-do list into to-do tasks 961 before departure and 962 tasks after arrival. The device 1000 determines a to-do 961 before departure for a trip as a first main task, and performs “reserving a plane ticket”, “reserving a lodging B”, “taking a passport photo” and “submitting a vacation plan” as the first It can be determined as a sub-task for the main task. Also, the device 1000 may determine the to-do 962 after arrival of the trip as the second main task, and determine “buy Susan gift” and “go to the XX festival” as sub-tasks for the second main task. As shown in FIG. 13 , the device 1000 is configured to “reserve a plane ticket”, “reserve a hotel B”, “take a passport photo” and “submit a vacation plan” which are sub-tasks for “to-dos before departure”. can be displayed separately from the subtasks "Buy Susan's Gift" and "Go to XX Festival" for "To Do After Travel Arrival".

Also, the device 1000 may display a link 971 for providing additional information related to the sub-task in the to-do list together with the sub-task.

14 is a diagram illustrating an example in which the device 1000 provides additional information related to a task in a to-do list, according to an embodiment.

Referring to FIG. 13 , a user may access an airplane reservation comparison site to make a reservation for an airplane ticket and compare prices for each airline. The device 1000 may also display information on "airplane reservation comparison site" at the bottom of "booking an airplane ticket". When the user selects "airplane reservation comparison site", as shown in FIG. 14 , the device 1000 may access the flight reservation comparison site. The user can compare flight ticket prices by airline by entering travel information on the flight reservation comparison site.

15 is a flowchart of a method of providing, by the device 1000, a task to replace a previously determined task, according to an exemplary embodiment.

In operation S610 , the device 1000 may obtain data related to the user's to-do list from a plurality of applications installed in the device 1000 and the server 2000 .

In detail, the device 1000 may obtain data about a call voice between a user and another user from a call application in the device 1000 . When a call application is executed and a call is connected between the user and another user, the device 1000 may record a call voice. The device 1000 may obtain the converted text by converting the recorded voice call into text. In addition, the device 1000 may transmit the recorded call voice to the server 2000 , and receive text changed from the call voice from the server 2000 .

Also, the device 1000 may obtain a message transmitted/received between the user and another user from the message application. The device 1000 may acquire a transmitted/received message as the device 1000 executes a message application in the device 1000 and transmits/receives a message to/from another user. The message application may include a chatting application, an SMS/MMS transmission/reception application, a messenger application, and an SNS application, but is not limited thereto. Also, the device 1000 may obtain the text of the email transmitted and received by the device 1000 . In this case, the device 1000 may obtain the text of the email from the executed web browser or the email transmission/reception application of the device 1000 .

Also, the device 1000 may acquire data about the user's schedule through the user's schedule management application installed in the device 1000 . In addition, the user may record the user's schedule information in the service providing server by using the service of the service providing server, and the device 1000 may receive the user's schedule information stored in the service providing server from the service providing server. In this case, the device 1000 may receive the user's schedule information from the service providing server by using the user ID of the service providing server. Also, the user may input the user's schedule information into the user's other device 1000 , and the device 1000 may obtain the user's memo information from the user's other device 1000 .

Also, the device 1000 may collect log information of an application executed in the device 1000 . The log information may indicate what operation the application executed on the device 1000 performed based on a user input. The device 1000 may acquire data used to determine whether a user performs a task by collecting log information regarding detailed operations of the executed application.

In operation S620 , the device 1000 may determine an alternative task for changing the previously determined task. The device 1000 may obtain data related to the first task in the to-do list and determine an alternative task for changing the first task. For example, it is assumed that the first task is "Today, go to a mart A near the house to shop". The device 1000 may acquire the information “A mart is closed today” from an application installed in the device 1000 or a service providing server subscribed by the user. In this case, the device 1000 obtains information of a B mart that can be visited near the user's house from an application installed in the device 1000 or a service providing server that the user has subscribed to, and goes to "Go to a B mart near the house today to go shopping". Alternate tasks can be determined.

Also, the device 1000 may determine whether a problem in which the user cannot perform other tasks in the to-do list may occur by changing the first task to another alternative task. If it is determined that a problem that prevents the user from performing another task will occur, the device 1000 may also determine an alternative task for the task in which the problem may occur.

In operation S630 , the device 1000 may display the determined replacement task. Also, the device 1000 may update the to-do list by changing the previously determined task to a replacement task. The device 1000 may output notification information regarding the replacement task before the point in time when the previously determined task is to be performed. The device 1000 may overlap the notification information on the execution screen of the display or output the notification information as a voice signal.

16 is a diagram illustrating an example in which the device 1000 provides a candidate task for a sub-task by identifying a user's intention, and provides an additional task for the determined task, according to an embodiment.

Referring to FIG. 16 , the device 1000 may display a message transmitted and received by the user (B) of the device 1000 and the user (microphone) of the external device through the message application on the execution screen of the message application. The device 1000 may send messages such as "Shall we go to Gangneung in August?", "Yes, but. How about August 12?", "Okay, how many days will we go?", "Let's go to 3 nights and 4 days" and Obtained the message "Let's go to a clean place, rent a car rental cheap" message, and based on the obtained message, the user (me) and the user of the external device (microphone) went to Gangneung on August 12 for 3 nights and 4 days This can be interpreted as preferring to go on a trip, to have a clean accommodation, and to rent a car for a cheap car. Accordingly, the device 1000 may determine “August 12”, “Gangneung”, “rental car”, “3 nights 4 days” and “lodging” as keywords based on the above analysis. The device 1000 may generate the determined keywords “August 12”, “Gangneung”, “rental car”, “3 nights 4 days” and “lodging” as a keyword list, and display it on the execution screen of the message application. . In this case, the device 1000 may display a GUI for editing at least one keyword in the keyword list on the execution screen of the display.

Also, the device 1000 may analyze the user's intention in the analysis. The device 1000 may determine a candidate task for the first keyword by applying the user's intention analysis result to the first keyword. The device 1000 may determine a candidate task by weighting factors capable of reflecting user intention, and may generate a list of candidate tasks.

Referring to FIG. 16 , the device 1000 performs “reservation of accommodation” based on the keyword list including “August 12”, “Gangneung”, “rental car”, “3 nights 4 days” and “accommodation”. and “Reserving a rental car” may be determined as a candidate task. In relation to "reserving accommodation", the device 1000 reflects the intention of the user (me) and the user (microphone) of the external device for a neat accommodation, and provides a list of accommodations listing accommodation information in the order of the highest rating to price. can provide In this case, the device 1000 may generate the lodging list by giving weight to the price and the rating. The device 1000 may acquire the lodging list from data stored in the device 1000 or from a service providing server to which the user has subscribed.

In addition, with respect to "reserving a rental car", the device 1000 reflects the intention of the user (me) and the user (microphone) of the external device to prefer a cheap car, and a car model with good car performance for each car rental company. We can provide a list of car rentals that list . The device 1000 may generate a rental car list by weighting the price and car performance. The device 1000 may obtain the rental car list from data stored in the device 1000 or from a service providing server to which the user has subscribed.

Also, the device 1000 may provide an additional task in consideration of a plurality of situations that may occur while the user performs a task in the to-do list. For example, as shown in FIG. 16 , while the user (B) and the user (microphone) of the external device travel to Gangneung, in consideration of a situation in which heat or rain weather will occur, the device 1000 is It is possible to provide a list of tasks that can be performed in case of weather (eg, A go to the beach, B to the beach, etc.), and a list of tasks that can be performed in rainy weather (eg, visit E restaurant, W places to visit, etc.).

17 is a diagram illustrating an example in which a device provides an alternative task to replace a sub task, according to an embodiment.

The device 1000 is configured to change at least one task in the to-do list based on data obtained by a plurality of applications installed in the device 1000 and data obtained from the service providing server 2000 to which the user is subscribed. One replacement task may be determined, and the task in the to-do list may be updated by reflecting the determined replacement task.

Referring to FIG. 17 , while the user travels to Jeju Island, the device 1000 may provide schedule information of the user. The user's travel schedule for the second day may consist of Jungmun Tourist Complex, Seogwipo Tourist Complex, Pyoseon Folk Village, Seopjikoji, and Seongsan Ilchulbong in the order. While checking the user's schedule, the device 1000 may acquire data indicating that a typhoon is scheduled to arrive in the Jungmun Tourist Complex area in the morning from a weather application installed in the device 1000 or a service server 2000 to which the user is subscribed.

The device 1000 may acquire data on a candidate place to replace the Jungmun Tourist Complex from an application installed in the device 1000 or a service server 2000 to which the user is subscribed. The device 1000 may determine Hallim Park, Gangjeong Amusement Park, Cheonjiyeon Falls, and Jeongbang Falls as replacement candidate locations based on the obtained data. In addition, the device 1000 may provide an optimal replacement location to the user based on data on each replacement candidate location. For example, the device 1000 may collect data on the distance from the accommodation, opening time, crowd concentration, weather, etc. for each replacement candidate location, and provide an optimal replacement location based on the collected data. . The device 1000 may assign a weight to each of the distance from the accommodation, the opening time, the degree of crowd concentration, and the weather, and calculate a rating. The device 1000 may provide “Hallym Park” having the highest rating than the reference value as an alternative place.

The device 1000 may change the “visit Jungmun Tourism Complex” task to a “visit Hallim Park” task in relation to the Jeju Island schedule, and update the task in the to-do list. The device 1000 may display an updated to-do list.

18 is a flowchart of a method of monitoring whether a task in a to-do list is performed by the device 1000 according to an exemplary embodiment.

In operation S710 , the device 1000 may obtain condition information used to determine whether a task in the to-do list has been performed.

The device 1000 may obtain condition information used to determine whether a task in the to-do list is performed from a plurality of applications installed in the device 1000 and data obtained from the server 2000 . In this case, the condition information is information used to determine whether a predetermined task has been performed, and may be preset. The condition information may include, but is not limited to, an application used to perform a predetermined task, user operation information related to the application, detailed operation information of the application according to the user's operation information, and the like.

That is, the device 1000 may determine detailed operations of the device 1000 for performing the first task in the to-do list and a relationship between the detailed operations.

In operation S720 , the device 1000 may monitor whether a task in the to-do list is performed based on condition information and information obtained from the device 1000 . The device 1000 may determine whether a task in the to-do list is performed based on condition information indicating a relationship between detailed operations of the device 1000 . The device 1000 may store first condition information used to determine whether the first task is performed. The device 1000 may monitor whether the first task is performed based on the information obtained from the device 1000 and the stored first condition information.

For example, if the first task is “buy water at the mart”, the device 1000 determines whether “buy water at the mart” is performed, based on the user's location information and/or the user's payment information can decide Here, the condition information may be location information of the user who arrived at the mart from the GPS application and/or payment information for the user's text message transmitted to the device 1000 .

Specifically, when the location information obtained from the GPS application is information indicating the location of the mart, and the text message information obtained from the message application includes "water payment details", the device 1000 may determine that the first task has been performed. .

In operation S730, the device 1000 may update the to-do list based on the monitoring result. As a result of monitoring of the device 1000 , if it is determined that a task in the to-do list has been performed, the device 1000 may delete the task performed in the to-do list. Also, as a result of monitoring of the device 1000 , if it is determined that the task in the to-do list has not been performed, the device 1000 may output notification information indicating that the task has not been performed.

19 is a diagram for describing a process of monitoring whether the device 1000 performs a task in a to-do list, according to an exemplary embodiment.

Referring to FIG. 19 , the device 1000 may obtain a message transmitted/received between the user of the device 1000 and the user of the external device through a message application in the device 1000 . The device 1000 may interpret the content of the obtained message as "a request from the user, Mr. Kim at work, to transmit the photos taken at the meeting held today". The device 1000 may add a task "Send a photo to Mr. Kim" to the user's to-do list.

The device 1000 may determine condition information used to determine whether the task of “sending a picture to Mr. Kim” is performed. For example, in the device 1000, the message application in the device 1000 is executed, the target to which the user transmits and receives a message is Sangsa Kim, and the device 1000 has an operation in which a photo is selected from the photo album in the device 1000. The case can be determined with condition information.

The device 1000 may monitor the operation of the application related to the user's behavior. The device 1000 may monitor whether a message application in the device 1000 is executed. When the device 1000 detects that the message application is being executed, the device 1000 may determine whether a target to which the user transmits and receives a message is Sangsa Kim, based on data obtained through the message application. When it is determined that the subject to which the user has transmitted and received the message is Sangsa Kim, the device 1000 may determine whether there was an operation of the device 1000 in which a photo was selected from a photo album in the device 1000 . When it is determined that there was an operation of the device 1000 in which a photo is selected from the photo album, the device 1000 may determine that the task of “sending a photo to Sangsa Kim” has been performed. In this case, the device 1000 may delete the task "Send a picture to Mr. Kim" from the user's to-do list. On the other hand, if even one condition information among the plurality of condition information is not satisfied, the device 1000 may determine that the task of “sending a picture to Mr. Kim” is not performed. In this case, the device 1000 may display a notification window of “Send a photo to Mr. Kim” through the execution screen of the display.

20 is a diagram for explaining a process of monitoring whether the device 1000 performs a task in a to-do list, according to another exemplary embodiment.

Referring to FIG. 20 , the device 1000 may add a “buy milk” task to the to-do list. The device 1000 may determine condition information used to determine whether the “buy milk” task is performed. For example, the device 1000 may obtain data representing the user's location information from the GPS application, and determine a case where the data representing the location information represents a location where a mart is located as condition information.

The device 1000 may monitor the operation of the application related to the user's behavior. The device 1000 may monitor data indicating the user's location information from a GPS application in the device 1000 in real time. When the device 1000 determines that the information indicating the location information indicates the location of the mart, the device 1000 may output notification information for the “buy milk” task. The device 1000 may display the notification information on the execution screen window of the display, and may output the notification information by voice. Also, when the device 1000 determines that the information indicating the location information indicates a location outside the mart, the device 1000 may output notification information on whether the “buy milk” task has been performed.

When the device 1000 sequentially acquires the data indicating the location of the mart and the data indicating the location outside the location of the mart from the GPS application, the device 1000 determines that the “buy milk” task has been performed, and the user's You can delete the "Buy Milk" task from your to-do list.

Also, when the device 1000 acquires data indicating a location out of the mart, the device 1000 outputs notification information on whether the “buy milk” task has been performed, and whether the “buy milk” task is performed from the user information can be received. The device 1000 may determine whether the “buy milk” task has been performed according to the information. When it is determined that the “buy milk” task has not been performed, the device 1000 may display a “buy milk” notification window through the execution screen of the display.

21 is a diagram for describing a process of monitoring whether the device 1000 performs a task in a to-do list, according to another exemplary embodiment.

Referring to FIG. 21 , the device 1000 may add a “buy milk” task to the to-do list. The device 1000 may determine condition information used to determine whether the “buy milk” task is performed. For example, the device 1000 may determine a case in which text message information obtained from the message application includes “milk payment history” as condition information.

The device 1000 may monitor the operation of the application related to the user's behavior. The device 1000 may monitor the user's payment details for text message information obtained from the message application in real time. When the device 1000 determines that the user's payment details include “milk payment” details, the device 1000 may determine that the “milk purchase” task has been performed.

Also, the device 1000 may output notification information on whether the “buy milk” task has been performed. The device 1000 may receive information on whether to perform the “buy milk” task from the user. The device 1000 may determine whether the “buy milk” task has been performed according to the information. When it is determined that the “buy milk” task has not been performed, the device 1000 may display a “buy milk” notification window through the execution screen of the display.

22 is a flowchart of a method in which the server 2000 determines a candidate task, the device 1000 generates a to-do list, and monitors whether a task in the to-do list is performed, according to an exemplary embodiment.

In operation S2200, the device 1000 may obtain data from an application executed on the display. Here, the data includes the contents of a call through the device 1000 , the contents of messages transmitted and received through the device 1000 , the contents of emails transmitted and received through the device 1000 , the contents of a memo recorded in the device 1000 , and the device 1000 . It may be data about the voice content recorded in the , the content of the user schedule stored in the device 1000, and the like, but is not limited thereto.

In operation S2205 , the device 1000 may transmit the obtained data to the server 2000 . The server 2000 may be a service providing server 2000 to which a user is subscribed. The service providing server 2000 may provide an SNS service, a message sending/receiving service, a communication service, a schedule management service, a content providing service, and a search service, but is not limited thereto.

In operation S2210, the server 2000 may determine at least one keyword used to determine at least one task to be performed by the user based on the obtained data. For example, the server 2000 may receive data regarding the content of the transmitted/received message and analyze the content of the message. The server 2000 may determine a keyword used to determine a task based on the analysis result. Also, the server 2000 may determine at least one keyword used to determine at least one task to be performed by the user based on the obtained data and data stored in the server 2000 .

In operation S2215 , the server 2000 may transmit the determined at least one keyword to the device 1000 .

In operation S2220, the device 1000 may generate a keyword list for at least one keyword. The device 1000 may display a GUI for selecting at least one of at least one keyword in the keyword list. The device 1000 may receive an input for modifying the keyword list through the GUI, and may generate a keyword list according to the input.

In operation S2225 , the device 1000 may transmit the keyword list to the server 2000 .

In operation S2230, the server 2000 may determine at least one candidate task based on the keyword list. The server 2000 may determine at least one candidate task based on the first keyword in the keyword list.

In operation S2235 , the server 2000 may transmit the determined at least one candidate task to the device 1000 .

In operation S2240 , the device 1000 may generate a to-do list to be performed by the user based on at least one candidate task. The device 1000 may generate a candidate task list for at least one candidate task, and generate a to-do list including at least one main task and at least one sub-task dependent on the main task based on the candidate task list. have.

In operation S2250, the device 1000 may monitor whether at least one task in the to-do list is performed. The device 1000 may obtain condition information used to determine whether at least one task in the to-do list has been performed, and monitor whether at least one task in the to-do list is performed based on the condition information.

In operation S2255, the device 1000 may update the task in the to-do list according to the monitoring result. For example, the device 1000 may delete the performed task from the to-do list. Also, the device 1000 may provide notification information about an unperformed task.

23 shows, according to another embodiment, the device 1000 generates a to-do list, the server 2000 determines a candidate task for determining a task in the to-do list, and monitors whether a task in the to-do list is performed. It is a flow chart of the method.

The operations of the device 1000 and the server 2000 according to steps S2200, SS2205, S2210, S2215, S2220, S2225, S2230, S2235 and S2240 shown in FIG. 23 are shown in FIG. The operation of the device 1000 and the server 2000 is the same.

In operation S2245 , the device 1000 may transmit information about the function of the application executed in the device 1000 to the server 2000 .

In operation S2250, the server 2000 may monitor whether at least one task in the to-do list is performed. The device 1000 may obtain condition information used to determine whether at least one task in the to-do list has been performed, and monitor whether at least one task in the to-do list is performed based on the condition information.

In step S2255, the server 2000 may update the task in the to-do list according to the monitoring result. For example, the server 2000 may delete the performed task from the to-do list.

In operation S2260 , the server 2000 may provide the updated to-do list to the device 1000 .

24 and 25 are block diagrams of a device 1000 in accordance with some embodiments.

24 , the device 1000 according to some embodiments may include a user input unit 1100 , an output unit 1200 , a processor 1300 , and a communication unit 1500 . However, not all of the components shown in FIG. 24 are essential components of the device 1000 . The device 1000 may be implemented by more components than those illustrated in FIG. 24 , or the device 1000 may be implemented by fewer components than those illustrated in FIG. 24 .

For example, as shown in FIG. 25 , the device 1000 according to some embodiments includes a sensing unit 1400 in addition to the user input unit 1100 , the output unit 1200 , the processor 1300 , and the communication unit 1500 . ), an A/V input unit 1600 , and a memory 1700 may be further included.

The user input unit 1100 means a means for a user to input data for controlling the device 1000 . For example, the user input unit 1100 includes a key pad, a dome switch, and a touch pad (contact capacitive method, pressure resistance film method, infrared sensing method, surface ultrasonic conduction method, integral type). There may be a tension measurement method, a piezo effect method, etc.), a jog wheel, a jog switch, and the like, but is not limited thereto.

The user input unit 1100 may receive a user input for requesting a response message to the user's voice input and executing an operation related to the response message.

The output unit 1200 may output an audio signal, a video signal, or a vibration signal, and the output unit 1200 may include a display unit 1210 , a sound output unit 1220 , and a vibration motor 1230 . have.

The display unit 1210 displays and outputs information processed by the device 1000 . For example, the display unit 1210 may display a user interface for requesting a response message to the user's voice input and executing an operation related to the response message.

The sound output unit 1220 outputs audio data received from the communication unit 1500 or stored in the memory 1700 . Also, the sound output unit 1220 outputs a sound signal related to a function (eg, a call signal reception sound, a message reception sound, and a notification sound) performed by the device 1000 .

The processor 1300 typically controls the overall operation of the device 1000 . For example, the processor 1300 executes programs stored in the memory 1700 , and thus the user input unit 1100 , the output unit 1200 , the sensing unit 1400 , the communication unit 1500 , and the A/V input unit 1600 . ) can be controlled in general. In addition, the processor 1300 may execute the programs stored in the memory 1700 to perform the functions of the device 1000 described in FIGS. 1 to 24 .

Specifically, the processor 1300 may determine at least one keyword used to determine at least one task to be performed by the user in the to-do list, based on data obtained by the application executed on the display unit 1210 . . The processor 1300 may generate a keyword list for the determined at least one keyword.

The processor 1300 may display a GUI for selecting at least one of at least one keyword in the keyword list by controlling the display unit 1210 . The processor 1300 may display a GUI for selecting at least one of at least one keyword in the keyword list by controlling the display to be superimposed on the execution screen of the executed application. For example, the application is a chatting application for communication with an external device, and at least one keyword may be extracted from text transmitted/received between the device and the external device.

The processor 1300 may receive an input for selecting a first keyword related to the first item from the keyword list through the GUI. The processor 1300 may determine at least one candidate task for the first item based on the selected first keyword. The processor 1300 may display a list of candidate tasks for at least one candidate task determined by controlling the display.

The processor 1300 combines all or part of the selected first keyword, data related to the first keyword acquired by at least one application installed in the device, and data related to the first keyword acquired from the service providing server to which the user is subscribed Thus, at least one candidate task for the first item may be determined.

The processor 1300 may display a GUI for editing the candidate task list by controlling the display. The processor 1300 may generate a to-do list including at least one main task and at least one sub-task dependent on the main task based on the candidate task list. The processor 1300 may determine at least one task in the to-do list based on at least one keyword selected through the GUI.

The processor 1300 is configured to change at least one task in the to-do list based on data obtained by at least one application different from the application executed on the display and data obtained from a service providing server to which the user is subscribed. can decide on a replacement task for The processor 1300 may display at least one alternative task by controlling the display unit 1210 .

The processor 1300 may obtain condition information used to determine whether at least one task in the to-do list has been performed, and monitor whether at least one task in the to-do list is performed based on the condition information. The processor 1300 may update the task in the to-do list based on the monitoring result.

In addition, the processor 1300 may determine the user's intention, provide related information, and recommend an alternative operation by using the data recognition model stored in the memory 1700 or the server 2000. 27 to 30 will be described in more detail.

The sensing unit 1400 may detect a state of the device 1000 or a state around the device 1000 , and transmit the sensed information to the processor 1300 .

The sensing unit 1400 includes a magnetic sensor 1410 , an acceleration sensor 1420 , a temperature/humidity sensor 1430 , an infrared sensor 1440 , a gyroscope sensor 1450 , and a position sensor. (eg, GPS) 1460 , a barometric pressure sensor 1470 , a proximity sensor 1480 , and at least one of an illuminance sensor 1490 , but is not limited thereto. Since a function of each sensor can be intuitively inferred from a person skilled in the art from the name, a detailed description thereof will be omitted.

The communication unit 1500 may include one or more components that allow the device 1000 to communicate with another apparatus (not shown) and the server 2000 . The other device (not shown) may be a computing device such as the device 1000 or a sensing device, but is not limited thereto. For example, the communication unit 1500 may include a short-range communication unit 1510 , a mobile communication unit 1520 , and a broadcast receiving unit 1530 .

Short-range wireless communication unit 151, Bluetooth communication unit, BLE (Bluetooth Low Energy) communication unit, short-range wireless communication unit (Near Field Communication unit), WLAN (Wi-Fi) communication unit, Zigbee (Zigbee) communication unit, infrared ( It may include an IrDA, infrared Data Association) communication unit, a Wi-Fi Direct (WFD) communication unit, an ultra wideband (UWB) communication unit, an Ant+ communication unit, and the like, but is not limited thereto.

The mobile communication unit 1520 transmits/receives a radio signal to and from at least one of a base station, an external terminal, and a server on a mobile communication network. Here, the wireless signal may include various types of data according to transmission/reception of a voice call signal, a video call signal, or a text/multimedia message.

The broadcast receiver 1530 receives a broadcast signal and/or broadcast-related information from the outside through a broadcast channel. The broadcast channel may include a satellite channel and a terrestrial channel. According to an implementation example, the device 1000 may not include the broadcast receiver 1530 .

Also, the communication unit 1500 may transmit/receive information necessary for requesting a response message to the user's voice input and executing an operation related to the response message, with another device (not shown) and the server 2000 .

The A/V (Audio/Video) input unit 1600 is for inputting an audio signal or a video signal, and may include a camera 1610 , a microphone 1620 , and the like. The camera 1610 may obtain an image frame such as a still image or a moving picture through an image sensor in a video call mode or a shooting mode. The image captured through the image sensor may be processed through the processor 1300 or a separate image processing unit (not shown). The image captured by the camera 1610 may be used as context information of the user.

The microphone 1620 receives an external sound signal and processes it as electrical voice data. For example, the microphone 1620 may receive an acoustic signal from an external device or a user. The microphone 1620 may receive a user's voice input. The microphone 1620 may use various noise removal algorithms for removing noise generated in the process of receiving an external sound signal.

The memory 1700 may store a program for processing and control of the processor 1300 , and may store data input to or output from the device 1000 .

The memory 1700 may include a flash memory type, a hard disk type, a multimedia card micro type, a card type memory (eg, SD or XD memory), and a RAM. (RAM, Random Access Memory) SRAM (Static Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory), magnetic memory, magnetic disk , may include at least one type of storage medium among optical disks.

Programs stored in the memory 1700 may be classified into a plurality of modules according to their functions, for example, may be classified into a UI module 1710 , a touch screen module 1720 , a notification module 1730 , and the like. .

The UI module 1710 may provide a specialized UI, GUI, and the like that interwork with the device 1000 for each application. The touch screen module 1720 may detect a touch gesture on the user's touch screen and transmit information about the touch gesture to the processor 1300 . The touch screen module 1720 according to some embodiments may recognize and analyze a touch code. The touch screen module 1720 may be configured as separate hardware including a controller.

The notification module 1730 may generate a signal for notifying the occurrence of an event in the device 1000 . Examples of the event generated in the device 1000 include call signal reception, message reception, key signal input, schedule notification, and the like. The notification module 1730 may output a notification signal in the form of a video signal through the display unit 1210 , may output a notification signal in the form of an audio signal through the sound output unit 1220 , and the vibration motor 1230 . It is also possible to output a notification signal in the form of a vibration signal through

26 is a block diagram of a server 2000 in accordance with some embodiments.

Referring to FIG. 26 , the server 2000 according to some embodiments may include a memory 2500 , a communication unit 270 , and a processor 2300 .

The memory 2500 may store data obtained by an application executed or installed in the device from the user's device. Also, the memory 2500 may store data related to a service subscribed to by the user of the device.

The communication unit 2700 may receive data obtained by an application executed or installed on the device from the user's device.

The processor 2300 may determine at least one keyword used to determine at least one task to be performed by the user in the to-do list based on data obtained from the device. The processor 2300 may determine at least one keyword by combining all or part of data obtained from the device and data stored in the server. Also, the processor 2300 may determine at least one candidate task related to at least one keyword based on data obtained from the device and data related to a service to which the user has subscribed.

Also, the processor 2300 may monitor whether at least one task in the to-do list has been performed based on condition information for determining whether a task in the to-do list has been performed. The processor 2300 may update the user's to-do list based on the monitoring result.

In addition, the communication unit 2700 includes at least one keyword used to determine a task in the user's to-do list, a keyword list for at least one keyword, at least one candidate task related to at least one keyword, and a list of candidate tasks , the updated to-do list can be transmitted to the device.

The processor 2300 typically controls the overall operation of the server 2000 . For example, the processor 2300 may control the memory 2500 and the communication unit 2700 as a whole by executing programs stored in the memory 2500 of the server 2000 . The processor 2300 may perform some of the operations of the device 1000 in FIGS. 1 to 24 by executing programs stored in the memory 2500 .

27 is a block diagram of a processor 1300 according to an embodiment.

Referring to FIG. 27 , the processor 1300 according to some embodiments may include a data learning unit 1310 and a data recognition unit 1320 .

The data learner 1310 may collect data used to determine a task in the user's to-do list from a plurality of applications installed in the device 1000 and the server 2000 . The data learning unit 1310 is a call application that transmits and receives a voice signal between the user's device and another user's device, a message application for communication between the user's device and another user's device, a user's email application, and a user's memo. Data to be used for learning to determine a task in the user's to-do list may be obtained from a memo application or a schedule management application for managing the user's schedule. The data learning unit 1310 may learn the data recognition model to analyze the collected data and have a criterion for determining a keyword used to determine a task in the user's to-do list.

In addition, the data learning unit 1310 may learn the data recognition model to analyze the collected data to determine the user's intention, and to have a standard for providing a task conforming to the user's intention. In addition, the data learning unit 1310 may learn the data recognition model to have a criterion for determining a substitutable task for the previously determined task.

Also, the data learning unit 1310 may learn the data recognition model to have a criterion for determining whether at least one task in the to-do list has been performed. The data learning unit 1310 determines a relationship between an application used to perform a predetermined task, user operation information related to the application, and detailed operation information of the application according to the user's operation information, and based on the determined relationship, data The recognition model may be trained to have a criterion for determining whether at least one task in the to-do list has been performed.

The data learning unit 1310 can learn the data recognition model to have a standard about which data to use to determine a task in the user's to-do list using the acquired data, and how to judge the situation using the data. have. The data learning unit 1310 may acquire data to be used for learning, and apply the acquired data to a data recognition model to be described later, so that the data recognition model may learn to have a criterion for situation determination.

The data recognition unit 1320 may determine a situation based on data. The data recognition unit 1320 may recognize a situation from predetermined data by using the learned data recognition model. The data recognition unit 1320 may determine a predetermined situation based on the predetermined data by acquiring predetermined data according to a preset criterion by learning, and using the data recognition model using the acquired data as an input value. . In addition, a result value output by the data recognition model using the obtained data as an input value may be used to update the data recognition model.

At least one of the data learning unit 1310 and the data recognition unit 1320 may be manufactured in the form of at least one hardware chip and mounted in an electronic device. For example, at least one of the data learning unit 1310 and the data recognition unit 1320 may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or a conventional general-purpose processor (eg, CPU). Alternatively, it may be manufactured as a part of an application processor) or a graphics-only processor (eg, GPU) and mounted on the various electronic devices described above.

In this case, the data learning unit 1310 and the data recognition unit 1320 may be mounted on one electronic device or may be mounted on separate electronic devices, respectively. For example, one of the data learning unit 1310 and the data recognition unit 1320 may be included in the electronic device, and the other may be included in the server. In addition, the data learning unit 1310 and the data recognition unit 1320 may provide the model information built by the data learning unit 1310 to the data recognition unit 1320 through wired or wireless communication, and the data recognition unit ( Data input to 1320 may be provided to the data learning unit 1310 as additional learning data.

Meanwhile, at least one of the data learning unit 1310 and the data recognition unit 1320 may be implemented as a software module. When at least one of the data learning unit 1310 and the data recognition unit 1320 is implemented as a software module (or a program module including an instruction), the software module is a computer-readable, non-transitory, non-transitory It may be stored in a readable recording medium (non-transitory computer readable media). Also, in this case, the at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, a part of the at least one software module may be provided by an operating system (OS), and the other part may be provided by a predetermined application.

28 is a block diagram of the data learning unit 1310 according to an exemplary embodiment.

Referring to FIG. 28 , the data learning unit 1310 according to some exemplary embodiments includes a data acquiring unit 1310-1, a preprocessing unit 1310-2, a training data selection unit 1310-3, and a model learning unit 1310. -4) and a model evaluation unit 1310-5.

However, this is only an exemplary embodiment, and the data learning unit 1310 may include some of the above-described components, or may further include other components in addition to the above-described components.

The data acquisition unit 1310-1 may acquire data necessary for situation determination. The data acquisition unit 1310-1 may acquire data necessary for learning for situation determination.

The data acquisition unit 1310-1 may acquire data on a call voice between the user and another user from a call application in the device 1000 . The data acquisition unit 1310-1 may record a call voice when a call application is executed and a call is connected between the user and another user. The data obtaining unit 1310-1 converts the recorded voice call into text to obtain the converted text. In addition, the data acquisition unit 1310-1 may transmit the recorded voice call to the server 2000 and receive text changed from the call voice from the server 2000 .

Also, the data acquisition unit 1310-1 may acquire a message transmitted/received between the user and another user from the message application. The data acquisition unit 1310-1 may acquire a transmitted/received message as the device 1000 executes a message application in the device 1000 and transmits/receives a message to/from another user. The message application may include a chatting application, an SMS/MMS transmission/reception application, a messenger application, and an SNS application, but is not limited thereto. Also, the data acquisition unit 1310-1 may acquire the text of the email transmitted and received by the device 1000 . In this case, the data acquisition unit 1310-1 may acquire the text of the email from the executed web browser or email transmission/reception application of the device 1000 .

Also, the data acquisition unit 1310-1 may acquire data about the user's schedule through the user's schedule management application installed in the device 1000 . In addition, the user may record the user's schedule information in the service providing server by using the service of the service providing server, and the data acquisition unit 1310-1 receives the user's schedule information stored in the service providing server from the service providing server. You may. In this case, the data obtaining unit 1310-1 may receive the user's schedule information from the service providing server by using the user ID of the service providing server. In addition, the user may input the user's schedule information into the user's other device 1000 , and the data acquisition unit 1310-1 may acquire the user's memo information from the user's other device 1000 .

Also, the data acquisition unit 1310-1 may collect log information of an application executed in the device 1000 . The log information may indicate what operation the application executed on the device 1000 performed based on a user input. The data acquisition unit 1310-1 may acquire data used to determine whether a user performs a task by collecting log information on detailed operations of the executed application.

The data acquisition unit 1310-1 may receive a moving image. A moving picture may be composed of a plurality of images (or frames). For example, the data acquisition unit 1310-1 may be configured to communicate with a camera of an electronic device including the data learning unit 1310 or an external camera (eg, CCTV or black) capable of communicating with the electronic device including the data learning unit 1310 . box, etc.) to receive video input. Here, the camera may include one or more image sensors (eg, a front sensor or a rear sensor), a lens, an image signal processor (ISP), or a flash (eg, an LED or a xenon lamp, etc.).

For example, the data acquisition unit 1310-1 may acquire voice data, image data, text data, or biosignal data. For example, the data acquisition unit 1310-1 may receive data through an input device (eg, a microphone, a camera, or a sensor) of the electronic device. Alternatively, the data acquisition unit 1310-1 may acquire data through an external device communicating with the electronic device.

The preprocessor 1310-2 is configured to determine a keyword used to determine a task in the user's to-do list, a criterion for providing a task that meets the user's intention, and a substitutable alternative task for the previously determined task. The acquired data may be pre-processed so that the acquired data can be used for learning for a criterion and a criterion for determining whether at least one task in the to-do list has been performed. The preprocessor 1310-2 may process the acquired data into a preset format so that the model learning unit 1310-4, which will be described later, uses the acquired data for learning to determine a task in the to-do list. .

The learning data selection unit 1310 - 3 may select data required for learning from among the preprocessed data. The selected data may be provided to the model learning unit 1310 - 4 . The learning data selection unit 1310-3 determines a keyword used to determine a task in the user's to-do list, determines the user's intention, recommends a replacement task for an existing task, and a preset criterion for monitoring whether the task is performed Accordingly, data necessary for learning can be selected from the preprocessed data. In addition, the training data selection unit 1310 - 3 may select data according to a preset criterion by learning by the model learning unit 1310 - 4 to be described later.

The model learning unit 1310-4 determines how the data recognition model determines the user's intention from the data collected based on the training data, how to determine candidate tasks, how to determine the replacement task for the existing task, and whether to perform the task. It is possible to learn to have a criterion for determining how to perform monitoring to determine . In addition, the model learning unit 1310-4 may learn the data recognition model to have a selection criterion for which learning data to use for determining the user's intention, determining the candidate task, determining the replacement task, and determining the monitoring of the task. have.

Also, the model learning unit 1310 - 4 may learn a data recognition model used for situation determination by using the training data. In this case, the data recognition model may be a pre-built model. For example, the data recognition model may be a model built in advance by receiving basic training data (eg, a sample image, etc.).

According to an embodiment, the model learning unit 1310-4 learns information related to at least one counterpart included in the contact application, such as message data, voice conversation data, log data, and the like, acquired by the data acquisition unit 1310 - 1 . Using data, the data recognition model can be trained to estimate the relationship between the acquired data and the counterpart. In this case, the data recognition model may use, for example, a relationship model.

For example, the model learning unit 1310-4 may learn about the relationship between a position appearing in the conversation content and a position included in the counterpart information by using the conversation content and the counterpart information included in the contact application as learning data.

According to an embodiment, the model learning unit 1310 - 4 selects at least one sentence, an interrogative word (eg, who, when, where, what, how, why), and a word corresponding to the interrogative word in the sentence. By using it as training data, the data recognition model can be trained to estimate keywords from the data. In this case, the data recognition model may include a natural language generation learning model (NLG).

According to an embodiment, the model learning unit 1310-4 may include a template (eg, sentence) or document, word corresponding to an item (work, daily life (eg, shopping, childcare, meal), travel, etc.) And by using a template or document to which the word is applied as training data, the data recognition model may be trained to estimate the task (or candidate task) from the keyword. In this case, the data recognition model may include a natural language processing learning model (NLP).

According to an embodiment, the model learning unit 1310 - 4 may use log data and the task of the device 1000 as training data to learn to estimate whether or not a task to be a data recognition model is performed.

Meanwhile, according to various embodiments, the data recognition models may be implemented as one data recognition model, or may be implemented as individual data recognition models, respectively.

The data recognition model may be constructed in consideration of the field of application of the recognition model, the purpose of learning, or the computer performance of the device. The data recognition model may be, for example, a model based on a neural network. For example, a model such as a deep neural network (DNN), a recurrent neural network (RNN), or a bidirectional recurrent deep neural network (BRDNN) may be used as the data recognition model, but is not limited thereto.

According to various embodiments, the model learning unit 1310 - 4 uses a data recognition model to learn a data recognition model having a high correlation between the input training data and the basic training data when there are a plurality of pre-built data recognition models. can decide In this case, the basic learning data may be pre-classified for each type of data, and the data recognition model may be previously built for each type of data. For example, the basic training data is pre-classified by various criteria such as the region where the training data is generated, the time when the training data is generated, the size of the training data, the genre of the training data, the creator of the training data, the type of object in the training data, etc. may have been

Also, the model learning unit 1310 - 4 may train the data recognition model using, for example, a learning algorithm including error back-propagation or gradient descent. .

Also, the model learning unit 1310 - 4 may train the data recognition model through, for example, supervised learning using learning data as an input value. In addition, the model learning unit 1310-4, for example, by self-learning the type of data required for situation determination without any guidance, determines the user's intention, determines the candidate task, determines the replacement task, and determines the monitoring of the task. A data recognition model can be trained through unsupervised learning to discover criteria for In addition, the model learning unit 1310 - 4 is, for example, reinforcement learning (reinforcement learning) using feedback on whether the results of determining the user's intention according to the learning, determining the candidate task, determining the replacement task, and determining the monitoring of the task are correct. ), it is possible to train a data recognition model.

Also, when the data recognition model is learned, the model learning unit 1310 - 4 may store the learned data recognition model. In this case, the model learning unit 1310 - 4 may store the learned data recognition model in the memory of the electronic device including the data recognition unit 1320 . Alternatively, the model learning unit 1310 - 4 may store the learned data recognition model in the memory of the electronic device including the data recognition unit 1320 to be described later. Alternatively, the model learning unit 1310 - 4 may store the learned data recognition model in a memory of a server connected to the electronic device through a wired or wireless network.

In this case, the memory in which the learned data recognition model is stored may also store, for example, commands or data related to at least one other component of the electronic device. The memory may also store software and/or programs. A program may include, for example, a kernel, middleware, an application programming interface (API) and/or an application program (or "application"), and the like.

The model evaluator 1310-5 may input evaluation data into the data recognition model, and when the recognition result output from the evaluation data does not satisfy a predetermined criterion, may cause the model learning unit 1310-4 to learn again. have. In this case, the evaluation data may be preset data for evaluating the data recognition model.

For example, the model evaluator 1310-5 sets a predetermined criterion when the number or ratio of the evaluation data for which the recognition result is not accurate among the recognition results of the learned data recognition model for the evaluation data exceeds a preset threshold. It can be evaluated as unsatisfactory. For example, when the predetermined criterion is defined as a ratio of 2%, when the learned data recognition model outputs an erroneous recognition result for more than 20 evaluation data out of a total of 1000 evaluation data, the model evaluation unit 1310-5 can be evaluated that the trained data recognition model is not suitable.

On the other hand, when there are a plurality of learned data recognition models, the model evaluation unit 1310 - 5 evaluates whether each learned video recognition model satisfies a predetermined criterion, and recognizes a model that satisfies the predetermined criterion as final data can be determined as a model. In this case, when there are a plurality of models satisfying the predetermined criteria, the model evaluator 1310 - 5 may determine any one or a predetermined number of models preset in the order of the highest evaluation score as the final data recognition model.

On the other hand, in the data learning unit 1310, the data acquisition unit 1310-1, the preprocessor 1310-2, the training data selection unit 1310-3, the model learning unit 1310-4, and the model evaluation unit 1310 At least one of -5) may be manufactured in the form of at least one hardware chip and mounted in an electronic device. For example, at least one of the data acquisition unit 1310-1, the preprocessor 1310-2, the training data selection unit 1310-3, the model learning unit 1310-4, and the model evaluation unit 1310-5 One may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or it may be manufactured as part of an existing general-purpose processor (eg, CPU or application processor) or graphics-only processor (eg, GPU) as described above. It may be mounted on various electronic devices.

In addition, the data acquisition unit 1310-1, the preprocessor 1310-2, the training data selection unit 1310-3, the model learning unit 1310-4, and the model evaluation unit 1310-5 are one electronic unit. It may be mounted on the device, or it may be mounted on separate electronic devices, respectively. For example, some of the data acquisition unit 1310-1, the preprocessor 1310-2, the training data selection unit 1310-3, the model learning unit 1310-4, and the model evaluation unit 1310-5 may be included in the electronic device, and the remaining part may be included in the server.

In addition, at least one of the data acquisition unit 1310-1, the preprocessor 1310-2, the training data selection unit 1310-3, the model learning unit 1310-4, and the model evaluation unit 1310-5 is It can be implemented as a software module. At least one of the data acquisition unit 1310-1, the preprocessor 1310-2, the training data selection unit 1310-3, the model learning unit 1310-4, and the model evaluation unit 1310-5 is a software module When implemented as (or, a program module including instructions), the software module may be stored in a computer-readable non-transitory computer readable medium. Also, in this case, the at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, a part of the at least one software module may be provided by an operating system (OS), and the other part may be provided by a predetermined application.

29 is a block diagram of the data recognition unit 1320 according to an exemplary embodiment.

Referring to FIG. 29 , the data recognition unit 1320 according to some embodiments includes a data acquisition unit 1320-1, a pre-processing unit 1320-2, a recognition data selection unit 1320-3, and a recognition result providing unit ( 1320-4) and a model update unit 1320-5.

However, this is only an embodiment, and the data recognition unit 1320 may include some of the above-described components, or may further include other components in addition to the above-described components.

The data acquisition unit 1320-1 may acquire recognition data necessary for determining the user's intention, determining the candidate task, determining the alternative task, and determining the monitoring of the task, and the preprocessor 1320-2 may determine the user's intention, The acquired data may be pre-processed so that the acquired recognition data may be used for candidate task determination, replacement task determination, and task monitoring determination.

According to an embodiment, the data acquisition unit 1320-1 may acquire data in the same manner as the data acquisition unit 1310-1 of the data learning unit 1310 described above with reference to FIG. 28 .

For example, the data acquisition unit 1320-1 may acquire the content of a conversation between the user and another user from the call application. Also, the data acquisition unit 1320-1 may acquire contents of messages transmitted and received between the user and other users from the message application. Also, the data acquisition unit 1320-1 may acquire data about the user's schedule through the user's schedule management application.

The preprocessing unit 1320-2 is configured so that the recognition result providing unit 1320-4, which will be described later, uses the acquired recognition data to determine a user's intention, determine a candidate task, determine an alternative task, and determine monitoring of a task. The recognition data may be processed into a preset format.

The recognition data selection unit 1320 - 3 may select recognition data necessary for determining the user's intention, determining the candidate task, determining the replacement task, and determining the monitoring of the task from among the pre-processed data. The selected recognition data may be provided to the recognition result providing unit 1320 - 4 . The recognition data selection unit 1320 - 3 may select some or all of the preprocessed recognition data according to preset criteria for determining the user's intention, determining the candidate task, determining the replacement task, and determining the monitoring of the task. Also, the recognition data selection unit 1320-3 may select recognition data according to a preset criterion by learning by the model learning unit 1310-4, which will be described later.

The recognition result providing unit 1320 - 4 may apply the selected recognition data to the data recognition model to determine the user's intention, the candidate task, the replacement task, and the monitoring of the task. The recognition result providing unit 1320 - 4 may provide a recognition result according to the recognition purpose of the recognition data. The recognition result providing unit 1320-4 may apply the selected recognition data to the data recognition model by using the recognition data selected by the recognition data selection unit 1320-3 as an input value. Also, the recognition result may be determined by a data recognition model.

According to an embodiment, the recognition result providing unit 1320 - 4 may use the text message content as recognition data and apply it to the data recognition model. The data recognition model may estimate words corresponding to interrogative words in text messages as keywords. Also, the recognition result providing unit 1320-4 may use the conversation content as recognition data and apply it to the data recognition model. The data recognition model may estimate words corresponding to interrogative words in conversation contents as keywords.

According to an embodiment, the recognition result providing unit 1320-4 may use the estimated keyword as recognition data and apply it to the data recognition model. The data recognition model may estimate a task (or candidate task) in the form of a sentence by applying a keyword to a template matched with at least one item.

According to an embodiment, the recognition result providing unit 1320 - 4 may use log data of the device 1000 as recognition data and apply it to the data recognition model. The data recognition model can check whether a task is performed using log data.

The model updating unit 1320 - 5 may update the data recognition model based on the evaluation of the recognition result provided by the recognition result providing unit 1320 - 4 . For example, the model updating unit 1320-5 provides the recognition result provided by the recognition result providing unit 1320-4 to the model learning unit 1310-4, so that the model learning unit 1310-4 is You can update the data recognition model.

On the other hand, in the data recognition unit 1320, the data acquisition unit 1320-1, the preprocessor 1320-2, the recognition data selection unit 1320-3, the recognition result providing unit 1320-4, and the model update unit ( 1320-5) may be manufactured in the form of at least one hardware chip and mounted in an electronic device. For example, among the data acquisition unit 1320-1, the preprocessor 1320-2, the recognition data selection unit 1320-3, the recognition result providing unit 1320-4, and the model update unit 1320-5 At least one may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI), or may be manufactured as part of an existing general-purpose processor (eg, CPU or application processor) or graphics-only processor (eg, GPU). It may be mounted on one various electronic devices.

In addition, the data acquisition unit 1320-1, the preprocessor 1320-2, the recognition data selection unit 1320-3, the recognition result providing unit 1320-4, and the model update unit 1320-5 are one It may be mounted on an electronic device, or may be respectively mounted on separate electronic devices. For example, among the data acquisition unit 1320-1, the preprocessor 1320-2, the recognition data selection unit 1320-3, the recognition result providing unit 1320-4, and the model update unit 1320-5 Some may be included in the electronic device, and some may be included in the server.

In addition, at least one of the data acquisition unit 1320-1, the preprocessor 1320-2, the recognition data selection unit 1320-3, the recognition result providing unit 1320-4, and the model update unit 1320-5 may be implemented as a software module. At least one of the data acquisition unit 1320-1, the preprocessor 1320-2, the recognition data selection unit 1320-3, the recognition result providing unit 1320-4, and the model update unit 1320-5 is software. When implemented as a module (or a program module including instructions), the software module may be stored in a computer-readable non-transitory computer readable medium. Also, in this case, the at least one software module may be provided by an operating system (OS) or may be provided by a predetermined application. Alternatively, a part of the at least one software module may be provided by an operating system (OS), and the other part may be provided by a predetermined application.

30 is a diagram illustrating an example of learning and recognizing data by interworking with the device 1000 and the server 2000 according to an embodiment.

Referring to FIG. 30 , the server 2000 may learn the data recognition model to have criteria for determining the user's intention, determining the candidate task, determining the replacement task, and determining the monitoring of the task. ) can judge the situation based on the learning results.

In this case, the model learning unit 2340 of the server 2000 may perform the function of the data learning unit 1310 illustrated in FIG. 28 . The model learning unit 2340 of the server 2000 determines what data the data recognition model uses to determine the user's intention, the candidate task, the alternative task, and the monitoring of the task, and how the data is used to determine the situation. You can learn to have a criterion for judging whether or not to do it. The model learning unit 2340 acquires data to be used for learning, and applies the acquired data to a data recognition model to be described later, thereby learning a selection criterion for determining a situation.

For example, the model learning unit 2340 may learn the data recognition model to analyze the collected data and have a criterion for determining a keyword used to determine a task in the user's to-do list. In addition, the model learning unit 2340 may learn the data recognition model to analyze the collected data to determine the user's intention, and to learn to have a standard for providing a task conforming to the user's intention. In addition, the model learning unit 2340 may learn the data recognition model to have a criterion for determining a substitutable task with respect to the previously determined task. Also, the model learning unit 2340 may learn the data recognition model to have a criterion for determining whether at least one task in the to-do list has been performed. The model learning unit 2340 determines the relationship between the application using the data recognition model to perform a predetermined task, the user's motion information related to the application, and the detailed motion information of the application according to the user's motion information, and the determined relationship It is possible to learn to have a criterion for determining whether at least one task in the to-do list has been performed based on the .

In addition, the recognition result providing unit 1320-4 of the device 1000 applies the data selected by the recognition data selection unit 1320-3 to the data recognition model generated by the server 2000 to determine the user's intention, Candidate task determination, replacement task determination, and task monitoring may be performed. For example, the recognition result providing unit 1320-4 transmits the data selected by the recognition data selection unit 1320-3 to the server 2000, and the server 2000 performs the recognition data selection unit 1320-3 By applying the selected data to the recognition model, it is possible to request user intention determination, candidate task determination, replacement task determination, and task monitoring. Also, the recognition result providing unit 1320 - 4 may receive information about the user's intention determined by the server 2000, the candidate task, the replacement task, and the monitoring result of the task from the server 2000 .

Alternatively, the recognition result providing unit 1320 - 4 of the device 1000 receives the recognition model generated by the server 2000 from the server 2000, and uses the received recognition model to determine the user's intention and to perform a candidate task. Decision, replacement task determination and task monitoring are possible. In this case, the recognition result providing unit 1320-4 of the device 1000 applies the data selected by the recognition data selection unit 1320-3 to the data recognition model received from the server 2000 to determine the user's intention, Candidate task determination, replacement task determination and task monitoring are possible.

In addition, the device 1000 and the server 2000 can effectively distribute and perform tasks for learning and data recognition of the data recognition model, and through this, data processing can be efficiently performed to provide a service that meets the user's intention. and can effectively protect the user's privacy.

31 is a flowchart of a method of managing a user's to-do list by the first processor 1300a and the second processor 1300b according to an exemplary embodiment.

According to an embodiment, the device 1000 may include a first processor 1300a and a second processor 1300b.

The first processor 1300a controls execution of at least one application installed in the device 1000 , performs graphic processing on an image acquired in the device 1000 , or data stored in the application (eg, text messages, voice chats, etc.). The first processor 1300a may be implemented in the form of a system on chip (SoC) in which functions such as a central processing unit (CPU), a graphic processing unit (GPU), a communication chip, and a sensor are integrated.

The second processor 1300b may estimate a keyword from data obtained from an application using a data recognition model, and may estimate a task (or a candidate task) in the user's to-do list using the estimated keyword.

Meanwhile, the second processor 1300b may be manufactured in the form of a dedicated hardware chip for artificial intelligence (AI) that performs a user to-do estimation function using a data recognition model. Also, the device 1000 may further include a third processor, a fourth processor, and the like that perform the same function as the second processor 1300b.

Meanwhile, according to various embodiments of the present disclosure, the function performed by the first processor 1300a is stored in the memory of the device 1000 and applications performing various functions may correspondingly perform the function, and the second processor 1300b ) may be performed correspondingly by an operating system (OS) of the device 1000 .

For example, the voice recognition application may recognize conversation content stored in the device 1000 and convert it into a text form. The voice recognition application may transmit the converted text or information related to the text to the operating system or an external server.

An operating system or an external server may estimate a keyword from a character using an included data recognition model, respectively.

In operation s3110 , the first processor 1300a may acquire data from an application executed on the device 1000 or from a server located outside the device 1000 .

For example, the first processor 1300a may obtain data used to generate the user's to-do list from a plurality of applications installed in the device 1000 . The acquired data may include, for example, the contents of a call through the device 1000 , the contents of messages transmitted/received through the device 1000 (eg, SMS, MMS, chatting message, E-mail, etc.), and the device 1000 . ) may be a voice memo recorded in ) and data related to a text file stored in the device 1000 , a photo, a video, user schedule content, memo, and the like. However, the type of data is not limited thereto.

In operation s3115, the first processor 1300a may transmit the acquired data to the second processor 1300b.

In operation s3120, the second processor 1300b may apply the acquired data to the data recognition model to estimate relevance to at least one counterpart included in the contact application.

For example, the data recognition model may estimate that data obtained from the call content is relevant to the counterpart in the contact application. In addition, the data recognition model may estimate that a person having a position included in the chatting message is related to a counterpart in the contact application.

In operation s3125, the second processor 1300b may estimate a keyword used to estimate a candidate task (or task) to be performed by the user by applying the obtained data to the data recognition model. For example, the second processor 1300b may apply the obtained data to a data recognition model set to estimate a keyword.

In operation s3130, the second processor 1300b may generate a keyword list by estimating at least one or more keywords.

In operation s3135 , the second processor 1300b may estimate a candidate task (or task) to be performed by the user by applying the keyword list to the data recognition model. For example, the second processor 1300b may apply the keyword list to a data recognition model set to estimate a candidate task. According to an embodiment, the second processor 1300b may estimate the candidate task to be in the form of a sentence indicating a task.

In operation s3140 , the second processor 1300b may transmit the estimated candidate task to the first processor 1300a.

In operation s3145, the first processor 1300a may generate a user's to-do list including at least one or more of the received candidate tasks, and control it to be displayed on a display or the like.

in step s3150. The second processor 1300b may estimate whether a task included in the to-do list is performed by using the log data of the device 1000 . For example, if the task is "buy water at the mart", the second processor 1300b may check whether the user's location is the same as the location of the mart using the GPS application included in the device 1000, and the device ( 1000), it is possible to check whether a payment text has been received in the text application included in the text application.

In operation s3155, the second processor 1300b may transmit information on whether the task is completed to the first processor 1300a.

In operation s3160, the first processor 1300a may update and display the to-do list according to the information on whether the task has been completed. For example, when it is determined that the to-do has been performed, the first processor 1300a may delete the task. Also, when it is determined that the to-do is not performed, the first processor 1300a may output notification information informing the user that the task has not been performed.

32 is a flowchart of a method of managing a user's to-do list by the first processor 1300a, the second processor 1300b, and the third processor 1300c according to an embodiment.

According to an embodiment, the device 1000 may include a first processor 1300a , a second processor 1300b , and a third processor 1300c .

In operation s3210 , the first processor 1300a may acquire data from an application executed on the device 1000 or from a server located outside the device 1000 .

In operation s3215, the first processor 1300a may transmit the acquired data to the second processor 1300b.

In operation s3220, the second processor 1300b may apply the acquired data to the data recognition model to estimate relevance with at least one counterpart included in the contact application.

In operation s3225, the second processor 1300b may estimate a keyword used to estimate a candidate task (or task) to be performed by the user by applying the obtained data to the data recognition model. The data recognition model may be, for example, a data recognition model configured to estimate keywords.

In operation s3230, the second processor 1300b may generate a keyword list by estimating at least one or more keywords.

In operation s3235 , the second processor 1300b may estimate a candidate task (or task) to be performed by the user by applying the keyword list to the data recognition model. The data recognition model may be, for example, a data recognition model configured to estimate a candidate task.

In operation s3240, the second processor 1300b may transmit the generated candidate task to the first processor 1300a.

In operation s3245 , the second processor 1300b may transmit the generated candidate task to the third processor 1300c.

In operation s3250, the first processor 1300a may generate a user's to-do list including at least one or more of the received candidate tasks, and control it to be displayed on a display or the like.

in step s3255. The third processor 1300c may estimate whether a task included in the to-do list is performed by using the log data of the device 1000 . For example, if the task is "buy water at the mart", the third processor 1300c may check whether the user's location is the same as the location of the mart using the GPS application included in the device 1000, and the device ( 1000), it is possible to check whether a payment text has been received in the text application included in the text application.

In operation s3260, the third processor 1300c may transmit information on whether the task is completed to the first processor 1300a.

In operation s3265 , the first processor 1300a may control the device 1000 to display an updated to-do list using information on whether a task is performed. For example, when it is determined that the to-do has been performed, the first processor 1300a may delete the task. Also, when it is determined that the to-do is not performed, the first processor 1300a may output notification information informing the user that the task has not been performed.

33 is a flowchart illustrating a situation in which a device manages a to-do list using a plurality of servers 2000a and 2000b according to an exemplary embodiment.

According to an embodiment, the device 1000 may manage the to-do list using the first server 2000a and the second server 2000b.

According to one embodiment, the server 2000 may be a computing device that provides a service to the device ( ), for example, a PC, a laptop, a mobile phone, a micro server, a global positioning system (GPS) device, an e-book terminal, home appliances and mobile computing devices. However, if not limited thereto, the server 2000 may include any type of device having a communication function and a data processing function.

Also, the device 1000 may be connected to the server 2000 through a network. In this case, the network includes a local area network (LAN), a wide area network (WAN), a value added network (VAN), a mobile radio communication network, a satellite communication network, and their mutual It may include a combination, and is a data communication network in a comprehensive sense that enables the device 1000 and the server 2000 to communicate smoothly with each other, and may include a wired Internet, a wireless Internet, and a mobile wireless communication network.

In operation s3310 , the device 1000 may acquire data from an application executed on the device 1000 .

In operation s3315 , the device 1000 may transmit the acquired data to the first server 2000a.

In operation s3320, the first server 2000a may apply the acquired data to the data recognition model to estimate relevance with at least one counterpart included in the contact application.

In operation s3325, the first server 2000a may determine a keyword used to estimate a candidate task (or task) to be performed by the user by applying the acquired data to the data recognition model. The data recognition model may be, for example, a data recognition model configured to estimate keywords.

In operation s3330, the first server 2000a may generate a keyword list by estimating at least one or more keywords.

In operation s3335, the first server 2000a may generate (or estimate) a candidate task (or task) to be performed by the user by applying the keyword list to the data recognition model. The data recognition model may be, for example, a data recognition model configured to estimate and generate a candidate task.

In operation S3340 , the first server 2000a may transmit the generated candidate task to the device 1000 .

In step s3345, the first server ( ) may transmit the generated candidate task to the second server (2000b).

In operation s3350, the device 1000 may generate a user's to-do list including at least one or more of the received candidate tasks, and control it to be displayed on a display or the like.

in step s3355. The second server 2000b may estimate whether a task included in the to-do list is performed by using the log data of the device 1000 . For example, if the task is "buy water at the mart", the second server 2000b may receive the GPS information of the device 1000 and check whether the user's location is the same as the location of the mart, and the device 1000 By receiving data related to the text application of

In operation s3360 , the second server 2000b may transmit information on whether the task is completed to the device 1000 .

In operation s3365, the device 1000 may display an updated to-do list using information on whether the task is performed. For example, when it is determined that the to-do has been performed, the device 1000 may delete the task. Also, when it is determined that the to-do is not performed, the device 1000 may output notification information informing the user that the task is not performed.

34 is a flowchart illustrating a situation in which a device manages a to-do list using the first processor 1300a, the second processor 1300b, and the server 2000 according to an embodiment.

In operation s3410 , the first processor 1300a may acquire data from an application executed in the device 1000 .

In operation s3415, the first processor 1300a may transmit the acquired data to the second processor 1300b.

In operation s3420, the second processor 1300b may apply the acquired data to the data recognition model to estimate relevance with at least one counterpart included in the contact application.

In operation s3425, the second processor 1300b may estimate a keyword used to estimate a candidate task (or task) to be performed by the user by applying the obtained data to the data recognition model. The data recognition model may be, for example, a data recognition model configured to estimate keywords.

In operation s3430, the second processor 1300b may generate a keyword list by estimating at least one or more keywords.

In operation s3435 , the second processor 1300b may estimate a candidate task (or task) to be performed by the user by applying the keyword list to the data recognition model. The data recognition model may be, for example, a data recognition model configured to estimate a candidate task.

In operation s3440 , the second processor 1300b may transmit the generated candidate task to the first processor 1300a.

In operation s3445 , the second processor 1300b may transmit the generated candidate task to the server 2000 .

In operation S3450, the first processor 1300a may generate a user's to-do list including at least one or more of the received candidate tasks, and may control the to-do list to be displayed on a display or the like.

in step s3455. The second processor 1300b may monitor whether a task included in the to-do list is performed. For example, if the task is "buy water at the mart", the third processor 1300c may check whether the user's location is the same as the location of the mart using the GPS application included in the device 1000, and the device ( 1000), it is possible to check whether a payment text has been received in the text application included in the text application.

In operation s3460, the second processor 1300b may transmit information on whether the task is completed to the first processor 1300a.

In step s3465, the first processor 1300a may update the to-do list according to the monitoring result. For example, when it is determined that the to-do has been performed, the first processor 1300a may delete the task. Also, when it is determined that the to-do is not performed, the first processor 1300a may output notification information informing the user that the task has not been performed.

In operation s3470 , the server 2000 may select an alternative task based on the environment information of the device 1000 . For example, when the schedule of “buy a gift at a department store” is a task, the server 2000 may obtain information that a department store is closed on a task execution date from a separate service server (eg, a department store server).

In this case, the server 2000 uses data obtained by clustering various tasks collected in the server 2000 to perform an alternative task such as “shopping using a department store application” among tasks belonging to the same cluster as “buying a gift at a department store”. can be selected.

In operation s3475, the server 2000 may transmit the selected replacement task to the first processor 1300a.

in step s3480. The first processor 1300a may change the to-do list by reflecting the replacement task, and control the changed to-do list to be displayed on the display.

Some embodiments may also be implemented in the form of a recording medium containing instructions executable by a computer, such as program modules executed by a computer. Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. In addition, computer-readable media may include both computer storage media and communication media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Communication media typically includes computer readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave, or other transport mechanism, and includes any information delivery media.

In addition, the disclosed embodiments may be implemented as a S/W program including instructions stored in a computer-readable storage medium.

A computer may include a device according to the disclosed embodiments as an apparatus capable of calling a stored instruction from a storage medium and operating according to the called instruction according to the disclosed embodiment.

The computer-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' means that the storage medium does not include a signal and is tangible, and does not distinguish that data is semi-permanently or temporarily stored in the storage medium.

In addition, the control method according to the disclosed embodiments may be provided included in a computer program product (computer program product). Computer program products may be traded between sellers and buyers as commodities.

The computer program product may include a S/W program and a computer-readable storage medium in which the S/W program is stored. For example, the computer program product may include a product (eg, a downloadable app) in the form of a S/W program distributed electronically through a device manufacturer or an electronic market (eg, Google Play Store, App Store). . For electronic distribution, at least a portion of the S/W program may be stored in a storage medium or may be temporarily generated. In this case, the storage medium may be a server of a manufacturer, a server of an electronic market, or a storage medium of a relay server temporarily storing a SW program.

The computer program product, in a system consisting of a server and a device, may include a storage medium of a server or a storage medium of a device. Alternatively, if there is a third device (eg, a smart phone) that is communicatively connected to the server or device, the computer program product may include a storage medium of the third device. Alternatively, the computer program product may include the S/W program itself transmitted from the server to the device or the third apparatus, or transmitted from the third apparatus to the device.

In this case, one of the server, the device and the third apparatus may execute the computer program product to perform the method according to the disclosed embodiments. Alternatively, two or more of a server, a device, and a third apparatus may execute a computer program product to distribute the method according to the disclosed embodiments.

For example, a server (eg, a cloud server or an artificial intelligence server, etc.) may execute a computer program product stored in the server to control a device communicatively connected with the server to perform the method according to the disclosed embodiments.

As another example, the third apparatus may execute a computer program product to control a device communicatively connected with the third apparatus to perform the method according to the disclosed embodiment. When the third device executes the computer program product, the third device may download the computer program product from the server and execute the downloaded computer program product. Alternatively, the third device may execute the computer program product provided in a preloaded state to perform the method according to the disclosed embodiments.

Also, in this specification, "unit" may be a hardware component such as a processor or circuit, and/or a software component executed by a hardware component such as a processor.

The foregoing description of the present invention is for illustration, and those of ordinary skill in the art to which the present invention pertains can understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and likewise components described as distributed may also be implemented in a combined form.

The scope of the present invention is indicated by the following claims rather than the above detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present invention. do.

Claims (21)

In a device that provides a user's to-do list (To Do List),
a communication unit for communicating with an external device;
display; and
A processor comprising:
determining at least one first keyword used to determine at least one task to be performed by the user in the to-do list based on first data obtained by a first application executed on the display;
determining at least one second keyword based on second data obtained from a second application related to the at least one first keyword;
controlling the display to display a keyword list including the determined at least one first keyword and the determined at least one second keyword;
receiving an input for selecting at least one keyword among the at least one first keyword and the at least one second keyword in the keyword list;
automatically create the at least one task from the to-do list based on the selected at least one keyword,
Determine at least one replacement task for deleting and replacing at least a portion of the at least one task of the to-do list based on third data obtained by the first application and a third application different from the second application do,
updating the to-do list by using the at least one replacement task to delete and replace at least a portion of the at least one task;
controlling the display to output the updated to-do list,
device.
According to claim 1,
The processor, by controlling the display, superimposes and displays the keyword list on the execution screen of the executed first application, the device.
According to claim 1,
The first application is a chatting application for communication with the external device, and the at least one first keyword is extracted from text transmitted and received between the device and the external device.
According to claim 1,
The processor receives an input for selecting a first keyword related to a first item from the keyword list, determines at least one candidate task for the first item based on the selected first keyword, and performs the display. Displaying a list of candidate tasks for the determined at least one candidate task by controlling.
5. The method of claim 4,
The processor includes all of the selected first keyword, data related to the first keyword acquired by at least one application installed in the device, and data related to the first keyword acquired from a service providing server to which the user is subscribed or some combination to determine at least one candidate task for the first item.
5. The method of claim 4,
wherein the processor displays a GUI for editing the candidate task list by controlling the display.
5. The method of claim 4,
The processor is configured to generate the to-do list including at least one main task and at least one sub-task dependent on the main task, based on the candidate task list.
delete According to claim 1,
The processor is configured to determine the at least one replacement task based on the third data obtained by the third application and the fourth data obtained from the service providing server to which the user is subscribed, and control the display. A device indicating at least one alternate task.
According to claim 1,
The processor obtains condition information used to determine whether the at least one task in the to-do list has been performed, and monitors whether the at least one task in the to-do list is performed based on the condition information, device.
11. The method of claim 10,
The processor is configured to update the task in the to-do list based on the monitoring result.
A method for a device to provide a user's to-do list, the method comprising:
acquiring first data used to generate the to-do list from a first application executed on a display of the device;
determining, based on the obtained first data, at least one first keyword used to determine at least one task to be performed by the user in the to-do list;
determining at least one second keyword based on second data obtained from a second application related to the at least one first keyword;
displaying a keyword list including the determined at least one first keyword and the determined at least one second keyword;
receiving an input for selecting at least one keyword among the at least one first keyword and the at least one second keyword in the keyword list;
automatically generating the at least one task from the to-do list based on the selected at least one keyword;
Determine at least one replacement task for deleting and replacing at least a portion of the at least one task of the to-do list based on third data obtained by the first application and a third application different from the second application to do;
updating the to-do list by using the at least one replacement task to delete and replace at least a portion of the at least one task; and
and outputting the updated to-do list.
13. The method of claim 12,
The displaying of the keyword list includes overlapping the keyword list on an execution screen of the executed first application and displaying the displayed keyword list.
13. The method of claim 12, wherein the method comprises:
receiving an input for selecting a first keyword related to a first item from the keyword list;
determining at least one candidate task for the first item based on the selected first keyword; and
The method further comprising the step of displaying a list of candidate tasks for the determined at least one candidate task.
15. The method of claim 14,
The method further comprising: based on the candidate task list, generating the to-do list including at least one main task and at least one sub-task dependent on the main task.
13. The method of claim 12, wherein determining the at least one replacement task comprises:
determining the at least one replacement task based on third data obtained by the third application and fourth data obtained from a service providing server to which the user is subscribed; and
and indicating the at least one alternate task.
13. The method of claim 12,
obtaining condition information used to determine whether the at least one task in the to-do list has been performed; and
The method further comprising: monitoring whether the at least one task in the to-do list is performed based on the condition information.
delete delete A computer-readable recording medium containing a program for executing a method for a device to provide a user's to-do list, the method comprising:
acquiring first data used to generate the to-do list from a first application executed on a display of the device;
determining, based on the obtained first data, at least one first keyword used to determine at least one task to be performed by the user in the to-do list;
determining at least one second keyword based on second data obtained from a second application related to the at least one first keyword;
displaying a keyword list including the determined at least one first keyword and the determined at least one second keyword;
receiving an input for selecting at least one keyword among the at least one first keyword and the at least one second keyword in the keyword list;
automatically generating the at least one task from the to-do list based on the selected at least one keyword;
Determine at least one replacement task for deleting and replacing at least a portion of the at least one task of the to-do list based on third data obtained by the first application and a third application different from the second application to do;
updating the to-do list by using the at least one replacement task to delete and replace at least a portion of the at least one task; and
Comprising the step of outputting the updated to-do list, a computer-readable recording medium. delete

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