KR102662988B1 - Method and apparatus for transmtting notification information to user - Google Patents

Abstract

According to an embodiment of the present disclosure, a method for transmitting notification information to a user, which is performed by a computing device, may be provided. The method includes obtaining first notification information about a first notification from a first application; Storing the first notification information in a notification database (DataBase, DB); Based on the first notification information, identifying a first user to receive the first notification; And transmitting a first message notifying that the first notification has been generated to a first user terminal corresponding to the first user, and the notification DB is based on the first time when the first notification occurred, The first notification information is stored in the form of a predetermined data structure, and the first user terminal can obtain the first notification information from the notification DB based on the first message.

Description

Method and apparatus for transmitting notification information to a user {METHOD AND APPARATUS FOR TRANSMTTING NOTIFICATION INFORMATION TO USER}

This disclosure relates to message transmission technology, and more specifically, to a method and device for transmitting notification information to a user.

With the recent development of online technology, the size of the web application market, which implements existing applications on a web browser, is growing. A web application refers to a software application that runs online through a web browser. These web applications can be accessed and used by users through an Internet browser, and can be provided in a web environment without separate installation or download. A web application can be composed of a front-end that is displayed on the user's web browser and a back-end that performs user information management and data processing on the server. Examples of programming languages used in the front end include HTML, CSS, and JavaScript.

Types of web applications include e-mail, social media, online banks, shopping sites, business collaboration tools, and games. Users can access web applications through a web browser, and web applications can provide various contents to users through data transmission and reception with a web server.

Republic of Korea Patent No. 10-1456624 (announced on November 4, 2014)

The present disclosure has been made in response to the above-described background technology, and seeks to provide a method and device for providing notification information to a user.

The technical problems of the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art from the description below.

According to an embodiment of the present disclosure to solve the above-described problem, a method of transmitting notification information to a user, which is performed by a computing device, may be provided. The method includes obtaining first notification information about a first notification from a first application; Storing the first notification information in a notification database (DataBase, DB); Based on the first notification information, identifying a first user to receive the first notification; And transmitting a first message notifying that the first notification has been generated to a first user terminal corresponding to the first user, and the notification DB is based on the first time when the first notification occurred, The first notification information is stored in the form of a predetermined data structure, and the first user terminal can obtain the first notification information from the notification DB based on the first message.

In one embodiment, the method includes obtaining second notification information regarding a second notification from a second application; storing the second notification information in a notification DB; Based on the second notification information, identifying the first user terminal to receive the second notification; It further includes transmitting a second message notifying that the second notification has been generated to the first user terminal, and the notification DB has the predetermined data structure based on a second time point when the second notification has been generated. The second notification information is stored in the form of, and the first user terminal can obtain the second notification information from the notification DB based on the second message.

In one embodiment, the first notification information includes first notification transmission information and first notification reception information, the first notification transmission information has a first notification ID as a key value, and the first notification A form of a data structure that has the first application ID (Identification) corresponding to the ID, the first sender ID, the first recipient ID, the first notification type, the first notification message data, and the first notification transmission time as attribute values. And the first notification reception information has the first notification ID and the first recipient ID as key values, and includes whether the first notification corresponding to the first notification ID has been read, whether the first notification has been deleted, and the first notification. It may be in the form of a data structure that has the read time and the first notification deletion time as attribute values.

In one embodiment, transmitting the first message includes, based on first notification information, identifying a plurality of users including the first user who will receive the first notification; And transmitting the first message notifying that the first notification has been generated to a user terminal corresponding to each of the plurality of users, and the first recipient ID is included in the room corresponding to the group chat room. It includes a plurality of user IDs corresponding to a plurality of users, and the user terminal corresponding to each of the plurality of users may obtain the first notification information from the notification DB based on the first message. .

In one embodiment, the first notification reception information is stored in a queue corresponding to the first recipient when the first recipient reads the first notification or deletes the first notification, And notifications can be stored in the queue according to the time order in which they were generated.

In one embodiment, the first application is mapped to an application platform corresponding to the first user terminal, and the first notification type includes a mention type, a schedule type, and a system type, and the mention type Notifications and the certain type of notification may be generated from a messenger application, and the system type notification may be generated from the application platform.

In one embodiment, the first application is mapped to an application platform corresponding to the first user terminal, and the first user terminal obtains the first notification information through a notification application mapped to the application platform. You can.

In one embodiment, the application platform is mapped to the first application and the second application, and the first application and the second application interact based on a preset interaction type between the first application and the second application. , On the application platform, first data generated in the first application and second data generated in the second application interact in a way that they are shared by each of the first application and the second application, and the preset interaction type is set based on application developer information, data type of data generated in the application, and category of application, and the data type may include personal information data, weather data, schedule data, message data, and game data. You can.

According to one aspect of the present disclosure, a computing device may be provided for transmitting notification information to a user. The computing device includes at least one processor; and a memory, wherein the at least one processor acquires first notification information regarding the first notification from the first application, stores the first notification information in a notification database (DataBase, DB), and stores the first notification information in a notification database (DataBase, DB). Based on notification information, identify a first user who will receive the first notification, and transmit a first message notifying that the first notification has occurred to a first user terminal corresponding to the first user, and The notification DB stores the first notification information in the form of a predetermined data structure based on the first time when the first notification occurs, and the first user terminal receives the information from the notification DB based on the first message. The first notification information can be obtained.

According to one aspect of the present disclosure, a computer program stored in a computer-readable storage medium may be provided. The computer program, when executed by one or more processors, causes the one or more processors to perform operations for transmitting a plurality of notification information to a user, the operations comprising: a first notification regarding a first notification from a first application; The act of obtaining information; An operation of storing the first notification information in a notification database (DataBase, DB); Identifying a first user to receive the first notification based on the first notification information; And an operation of transmitting a first message notifying that the first notification has been generated to a first user terminal corresponding to the first user, and the notification DB is based on the first time when the first notification is generated, The first notification information is stored in the form of a predetermined data structure, and the first user terminal can obtain the first notification information from the notification DB based on the first message.

The present disclosure can provide a method and device for providing notification information to a user.

The effects that can be obtained from the present disclosure are not limited to the effects mentioned above, and other effects not mentioned can be clearly understood by those skilled in the art from the description below. .

Various aspects will now be described with reference to the drawings, where like reference numerals are used to collectively refer to like elements. In the following examples, for purposes of explanation, numerous specific details are set forth to provide a comprehensive understanding of one or more aspects. However, it will be clear that such aspect(s) may be practiced without these specific details.
FIG. 1 is a diagram illustrating a computing device for transmitting a message to a plurality of users according to an embodiment of the present disclosure.
Figure 2 is a diagram showing an exemplary structure of an artificial intelligence-based model according to an embodiment of the present disclosure.
FIG. 3 is a flowchart illustrating a method for providing notification information to a user, performed on a computing device according to an embodiment of the present disclosure.
FIG. 4 is a diagram illustrating a process in which a user obtains notification information from a plurality of applications according to an embodiment of the present disclosure.
Figure 5 depicts a brief, general schematic diagram of an example computing environment in which embodiments of the present disclosure may be implemented.

Various embodiments are now described with reference to the drawings. In this specification, various descriptions are presented to provide an understanding of the disclosure. However, it is clear that these embodiments may be practiced without these specific descriptions.

As used herein, the terms “component,” “module,” “system,” and the like refer to a computer-related entity, hardware, firmware, software, a combination of software and hardware, or an implementation of software. For example, a component may be, but is not limited to, a process running on a processor, a processor, an object, a thread of execution, a program, and/or a computer. For example, both an application running on a computing device and the computing device can be a component. One or more components may reside within a processor and/or thread of execution. A component may be localized within one computer. A component may be distributed between two or more computers. Additionally, these components can execute from various computer-readable media having various data structures stored thereon. Components may transmit signals, for example, with one or more data packets (e.g., data and/or signals from one component interacting with other components in a local system, a distributed system, to other systems and over a network such as the Internet). Depending on the data being transmitted, they may communicate through local and/or remote processes.

Additionally, the term “or” is intended to mean an inclusive “or” and not an exclusive “or.” That is, unless otherwise specified or clear from context, “X utilizes A or B” is intended to mean one of the natural implicit substitutions. That is, either X uses A; X uses B; Or, if X uses both A and B, “X uses A or B” can apply to either of these cases. Additionally, the terms “or”, “and/or” as used herein should be understood to refer to and include all possible combinations of one or more of the related items listed.

Additionally, the terms “comprise” and/or “comprising” should be understood to mean that the corresponding feature and/or element is present. However, the terms “comprise” and/or “comprising” should be understood as not excluding the presence or addition of one or more other features, elements and/or groups thereof. Additionally, unless otherwise specified or the context is clear to indicate a singular form, the singular terms herein and in the claims should generally be construed to mean “one or more.”

And, the term “at least one of A or B” should be interpreted to mean “a case containing only A,” “a case containing only B,” and “a case of combining A and B.”

Those skilled in the art will additionally recognize that the various illustrative logical blocks, components, modules, circuits, means, logic, and algorithm steps described in connection with the embodiments disclosed herein may be implemented using electronic hardware, computer software, or a combination of both. It must be recognized that it can be implemented with To clearly illustrate the interchangeability of hardware and software, various illustrative components, blocks, configurations, means, logics, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented in hardware or software will depend on the specific application and design constraints imposed on the overall system. A skilled technician can implement the described functionality in a variety of ways for each specific application. However, such implementation decisions should not be construed as causing a departure from the scope of the present disclosure.

The description of the presented embodiments is provided to enable anyone skilled in the art to use or practice the present invention. Various modifications to these embodiments will be apparent to those skilled in the art. The general principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Therefore, the present invention is not limited to the embodiments presented herein. The present invention is to be interpreted in the broadest scope consistent with the principles and novel features presented herein.

In the present disclosure, terms expressed as N-th, such as first, second, or third, may be used to distinguish different or corresponding entities from each other. For example, the entities expressed as first and second may be the same or different from each other. N may be a natural number.

FIG. 1 is a diagram illustrating a computing device for transmitting a message to a plurality of users according to an embodiment of the present disclosure.

Referring to FIG. 1 , the computing device 100 may include a processor 110, a memory 130, and a network unit 150. The configuration of the computing device 100 shown in FIG. 1 is only a simplified example, and in one embodiment, the computing device 100 may include other configurations or may include only some of the disclosed configurations.

The processor 110 may consist of one or more cores, and the computing device 100 may include a central processing unit (CPU), a general purpose graphics processing unit (GPGPU), and a tensor processing unit (TPU). : tensor processing unit) may include a processor to perform operations related to data processing.

According to an embodiment of the present disclosure, the processor 110 may perform calculations for learning an artificial intelligence-based model. For example, the processor 110 processes input data for learning in deep learning (DL), extracts features from input data, calculates errors, and weights an artificial intelligence-based model using backpropagation. Calculations for learning neural networks, such as updates, can be performed. The processor 110 may process learning of network functions. Additionally, in one embodiment, the processor 110 may perform network function learning and network function data processing by using processors of a plurality of computing devices together.

The processor 110 may typically control the overall operation of the computing device 100. The processor 110 provides appropriate information or functions to the user by processing signals, data, information, etc. input or output through components included in the computing device 100 or running an application program stored in the memory 130. Or you can process it.

According to one embodiment, the memory 130 may store any type of information generated or determined by the processor 110 and/or any type of information received by the network unit 150. Memory 130 may be operated by processor 110.

According to one embodiment, the memory 130 is a flash memory type, hard disk type, multimedia card micro type, card type memory (for example, SD or XD memory, etc.), RAM (Random Access Memory), SRAM (Static Random Access Memory), ROM (Read-Only Memory, ROM), EEPROM (Electrically Erasable Programmable Read-Only Memory), PROM (Programmable Read-Only Memory) ), it may include at least one type of storage medium among magnetic memory, magnetic disk, and/or optical disk. The computing device 100 may operate in connection with web storage that performs a storage function of the memory 130 on the Internet. The description of the memory described above is merely an example, and the present disclosure is not limited thereto.

The network unit 150 according to an embodiment of the present disclosure may use any type of wired or wireless communication system.

In the present disclosure, the network unit 150 may be configured regardless of the communication mode, such as wired or wireless, and may be composed of various communication networks such as a personal area network (PAN) and a wide area network (WAN). You can. Additionally, the network may be the well-known World Wide Web (WWW), and may also use wireless transmission technology used for short-distance communication, such as Infrared Data Association (IrDA) or Bluetooth. The techniques described in this disclosure may also be used in other networks mentioned above.

Figure 2 is a diagram showing an exemplary structure of an artificial intelligence-based model according to an embodiment of the present disclosure.

Throughout this specification, artificial intelligence model, artificial intelligence-based model, computational model, neural network, network function, and neural network may be used with the same meaning.

A neural network can generally consist of a set of interconnected computational units, which can be referred to as nodes. These nodes may also be referred to as neurons. A neural network consists of at least one node. Nodes (or neurons) that make up neural networks may be interconnected by one or more links.

Within a neural network, one or more nodes connected through a link may form a relative input node and output node relationship. The concepts of input node and output node are relative, and any node in an output node relationship with one node may be in an input node relationship with another node, and vice versa. As described above, input node to output node relationships can be created around links. One or more output nodes can be connected to one input node through a link, and vice versa.

In a relationship between an input node and an output node connected through one link, the value of the data of the output node may be determined based on the data input to the input node. Here, the link connecting the input node and the output node may have a weight. Weights may be variable and may be varied by the user or algorithm in order for the neural network to perform the desired function. For example, when one or more input nodes are connected to one output node by respective links, the output node is set to the values input to the input nodes connected to the output node and the links corresponding to each input node. The output node value can be determined based on the weight.

As described above, in a neural network, one or more nodes are interconnected through one or more links to form an input node and output node relationship within the neural network. The characteristics of the neural network may be determined according to the number of nodes and links within the neural network, the correlation between the nodes and links, and the value of the weight assigned to each link. For example, if the same number of nodes and links exist and two neural networks with different weight values of the links exist, the two neural networks may be recognized as different from each other.

A neural network may consist of a set of one or more nodes. A subset of nodes that make up a neural network can form a layer. Some of the nodes constituting the neural network may form one layer based on the distances from the first input node. For example, a set of nodes with a distance n from the initial input node may constitute n layers. The distance from the initial input node can be defined by the minimum number of links that must be passed to reach the node from the initial input node. However, this definition of a layer is arbitrary for explanation purposes, and the order of a layer within a neural network may be defined in a different way than described above. For example, a layer of nodes may be defined by distance from the final output node.

In one embodiment of the present disclosure, a set of neurons or nodes may be defined by the expression layer.

The initial input node may refer to one or more nodes in the neural network through which data is directly input without going through links in relationships with other nodes. Alternatively, in the relationship between nodes based on links within a neural network, it may refer to nodes that do not have other input nodes connected by links. Similarly, the final output node may refer to one or more nodes that do not have an output node in their relationship with other nodes among the nodes in the neural network. Additionally, hidden nodes may refer to nodes constituting a neural network other than the first input node and the last output node.

The neural network according to an embodiment of the present disclosure is a neural network in which the number of nodes in the input layer may be the same as the number of nodes in the output layer, and the number of nodes decreases and then increases again as it progresses from the input layer to the hidden layer. You can. In addition, the neural network according to another embodiment of the present disclosure may be a neural network in which the number of nodes in the input layer may be less than the number of nodes in the output layer, and the number of nodes decreases as it progresses from the input layer to the hidden layer. there is. In addition, the neural network according to another embodiment of the present disclosure may be a neural network in which the number of nodes in the input layer may be greater than the number of nodes in the output layer, and the number of nodes increases as it progresses from the input layer to the hidden layer. You can. A neural network according to another embodiment of the present disclosure may be a neural network that is a combination of the above-described neural networks.

A deep neural network (DNN) may refer to a neural network that includes multiple hidden layers in addition to the input layer and output layer. Deep neural networks allow you to identify latent structures in data. That is, the potential structure of a photo, text, video, voice, protein sequence structure, gene sequence structure, peptide sequence structure, music (e.g., which object is in the photo, what is the content and emotion of the text, the voice (what the content and emotions are, etc.), and/or the binding affinity between the peptide and MHC. Deep neural networks include convolutional neural network (CNN), recurrent neural network (RNN), auto encoder, restricted Boltzmann machine (RBM), and deep trust network ( It may include deep belief network (DBN), Q network, U network, Siamese network, generative adversarial network (GAN), transformer, etc. The description of the deep neural network described above is only an example and the present disclosure is not limited thereto.

The artificial intelligence-based model of the present disclosure can be expressed by a network structure of any of the structures described above, including an input layer, a hidden layer, and an output layer.

Neural networks that can be used in the artificial intelligence-based model of the present disclosure include supervised learning, unsupervised learning, semi-supervised learning, transfer learning, and active learning. It can be learned using at least one of: learning or reinforcement learning. Learning of a neural network may be a process of applying knowledge for the neural network to perform a specific operation to the neural network.

Neural networks can be trained to minimize output errors. In neural network learning, learning data is repeatedly input into the neural network, the output of the neural network and the error of the target for the learning data are calculated, and the error of the neural network is transferred from the output layer of the neural network to the input layer in the direction of reducing the error. This is the process of updating the weight of each node in the neural network through backpropagation. In the case of supervised learning, training data in which the correct answer is labeled for each training data is used (i.e., labeled training data), and in the case of unsupervised learning, the correct answer may not be labeled in each training data. That is, for example, in the case of supervised learning on data classification, the training data may be data in which each training data is labeled with a category. Labeled training data is input to the neural network, and the error can be calculated by comparing the output (category) of the neural network with the label of the training data. As another example, in the case of unsupervised learning on data classification, the error can be calculated by comparing the input training data with the neural network output. The calculated error is backpropagated in the reverse direction (i.e., from the output layer to the input layer) in the neural network, and the connection weight of each node in each layer of the neural network can be updated according to backpropagation. The amount of change in the connection weight of each updated node may be determined according to the learning rate. The neural network's calculation of input data and backpropagation of errors can constitute a learning cycle (epoch). The learning rate may be applied differently depending on the number of repetitions of the learning cycle of the neural network. For example, in the early stages of neural network training, a high learning rate can be used to increase efficiency by allowing the neural network to quickly achieve a certain level of performance, and in the later stages of training, a low learning rate can be used to increase accuracy.

In the learning of neural networks, the training data can generally be a subset of real data (i.e., the data to be processed using the learned neural network), and thus the error for the training data is reduced, but the error for the real data is reduced. There may be an incremental learning cycle. Overfitting is a phenomenon in which errors in actual data increase due to excessive learning on training data. For example, a phenomenon in which a neural network that learned a cat by showing a yellow cat fails to recognize that it is a cat when it sees a non-yellow cat may be a type of overfitting. Overfitting can cause errors in machine learning algorithms to increase. To prevent such overfitting, various optimization methods can be used. To prevent overfitting, methods such as increasing the training data, regularization, dropout to disable some of the network nodes during the learning process, and use of a batch normalization layer are used. It can be applied.

A computer-readable medium storing a data structure according to an embodiment of the present disclosure is disclosed. The above-described data structure can be stored in a storage unit in the present disclosure, executed by a processor, and transmitted and received by a communication unit.

Data structure can refer to the organization, management, and storage of data to enable efficient access and modification of data. Data structure can refer to the organization of data to solve a specific problem (e.g., data analysis, data retrieval, data storage, data modification). A data structure may be defined as a physical or logical relationship between data elements designed to support a specific data processing function. Logical relationships between data elements may include connection relationships between user-defined data elements. Physical relationships between data elements may include actual relationships between data elements that are physically stored in a computer-readable storage medium (e.g., a persistent storage device). A data structure may specifically include a set of data, relationships between data, and functions or instructions applicable to the data. Effectively designed data structures allow computing devices to perform computations while minimizing the use of the computing device's resources. Specifically, computing devices can increase the efficiency of operations, reading, insertion, deletion, comparison, exchange, and retrieval through effectively designed data structures.

Data structures can be divided into linear data structures and non-linear data structures depending on the type of data structure. A linear data structure may be a structure in which only one piece of data is connected to another piece of data. Linear data structures may include List, Stack, Queue, and Deque. A list can refer to a set of data that has an internal order. The list may include a linked list. A linked list may be a data structure in which data is connected in such a way that each data is connected in a single line with a pointer. In a linked list, a pointer may contain connection information to the next or previous data. Depending on its form, a linked list can be expressed as a singly linked list, a doubly linked list, or a circularly linked list. A stack may be a data listing structure that allows limited access to data. A stack can be a linear data structure in which data can be processed (for example, inserted or deleted) at only one end of the data structure. Data stored in the stack may have a data structure (LIFO-Last in First Out) where the later it enters, the sooner it comes out. A queue is a data listing structure that allows limited access to data. Unlike the stack, it can be a data structure (FIFO-First in First Out) where data stored later is released later. A deck can be a data structure that can process data at both ends of the data structure.

A non-linear data structure may be a structure in which multiple pieces of data are connected behind one piece of data. Nonlinear data structures may include graph data structures. A graph data structure can be defined by vertices and edges, and an edge can include a line connecting two different vertices. Graph data structure may include a tree data structure. A tree data structure may be a data structure in which there is only one path connecting two different vertices among a plurality of vertices included in the tree. In other words, it may be a data structure that does not form a loop in the graph data structure.

Throughout this specification, the terms artificial intelligence-based model, computational model, neural network, network function, and neural network may be used interchangeably. Below, it is described in a unified manner as a neural network. Data structures may include neural networks. And the data structure including the neural network may be stored in a computer-readable medium. Data structures including neural networks also include data preprocessed for processing by a neural network, data input to the neural network, weights of the neural network, hyperparameters of the neural network, data acquired from the neural network, activation functions associated with each node or layer of the neural network, neural network It may include a loss function for learning. A data structure containing a neural network may include any of the components disclosed above. In other words, the data structure including the neural network includes preprocessed data for processing by the neural network, data input to the neural network, weights of the neural network, hyperparameters of the neural network, data acquired from the neural network, activation functions associated with each node or layer of the neural network, neural network It may be configured to include all or any combination of loss functions for learning. In addition to the configurations described above, a data structure containing a neural network may include any other information that determines the characteristics of the neural network. Additionally, the data structure may include all types of data used or generated in the computational process of a neural network and is not limited to the above. Computer-readable media may include computer-readable recording media and/or computer-readable transmission media. A neural network can generally consist of a set of interconnected computational units, which can be referred to as nodes. These nodes may also be referred to as neurons. A neural network consists of at least one node.

The data structure may include data input to the neural network. A data structure containing data input to a neural network may be stored in a computer-readable medium. Data input to the neural network may include learning data input during the neural network learning process and/or input data input to the neural network on which training has been completed. Data input to the neural network may include data that has undergone pre-processing and/or data subject to pre-processing. Preprocessing may include a data processing process to input data into a neural network. Therefore, the data structure may include data subject to preprocessing and data generated by preprocessing. The above-described data structure is only an example and the present disclosure is not limited thereto.

The data structure may include the weights of the neural network. (In this specification, weights and parameters may be used interchangeably.) And the data structure including the weights of the neural network may be stored in a computer-readable medium. A neural network may include multiple weights. Weights may be variable and may be varied by the user or algorithm in order for the neural network to perform the desired function. For example, when one or more input nodes are connected to one output node by respective links, the output node is set to the values input to the input nodes connected to the output node and the links corresponding to each input node. Based on the weight, the data value output from the output node can be determined. The above-described data structure is only an example and the present disclosure is not limited thereto.

As an example and not a limitation, the weights may include weights that are changed during the neural network learning process and/or weights for which neural network learning has been completed. Weights that change during the neural network learning process may include weights that change at the start of the learning cycle and/or weights that change during the learning cycle. Weights for which neural network training has been completed may include weights for which a learning cycle has been completed. Therefore, the data structure including the weights of the neural network may include weights that are changed during the neural network learning process and/or the data structure including the weights for which neural network learning has been completed. Therefore, the above-mentioned weights and/or combinations of each weight are included in the data structure including the weights of the neural network. The above-described data structure is only an example and the present disclosure is not limited thereto.

The data structure including the weights of the neural network may be stored in a computer-readable storage medium (e.g., memory, hard disk) after going through a serialization process. Serialization can be the process of converting a data structure into a form that can be stored on the same or a different computing device and later reorganized and used. Computing devices can transmit and receive data over a network by serializing data structures. Data structures containing the weights of a serialized neural network can be reconstructed on the same computing device or on a different computing device through deserialization. The data structure including the weights of the neural network is not limited to serialization. Furthermore, the data structure including the weights of the neural network is a data structure to increase computational efficiency while minimizing the use of computing device resources (e.g., B-Tree, R-Tree, Trie, m-way search tree in non-linear data structures). , AVL tree, Red-Black Tree). The foregoing is merely an example and the present disclosure is not limited thereto.

The data structure may include hyper-parameters of a neural network. And the data structure including the hyperparameters of the neural network can be stored in a computer-readable medium. A hyperparameter may be a variable that can be changed by the user. Hyperparameters include, for example, learning rate, cost function, number of learning cycle repetitions, weight initialization (e.g., setting the range of weight values subject to weight initialization), Hidden Unit. It may include a number (e.g., number of hidden layers, number of nodes in hidden layers). The above-described data structure is only an example and the present disclosure is not limited thereto.

FIG. 3 is a flowchart illustrating a method for providing notification information to a user, performed on a computing device according to an embodiment of the present disclosure.

In step S310, the computing device 100 may obtain first notification information regarding the first notification from the first application. For example, the first application may be a web application. In one embodiment, the first notification information may include first notification transmission information and first notification reception information. The first notification transmission information has the first notification ID as a key value, the first application ID (Identification) corresponding to the first notification ID, the first sender ID, the first recipient ID, the first notification type, and the first notification ID. 1 It may be in the form of a data structure that has notification message data and the first notification transmission time as attribute values. The first notification reception information has the first notification ID and the first recipient ID as key values, and includes whether the first notification corresponding to the first notification ID has been read, whether the first notification has been deleted, the first notification reading time, and the first notification deletion. It may be in the form of a data structure that has time as an attribute value.

In step S320, the computing device 100 may store the first notification information in a notification database (DataBase, DB). In one embodiment, the notification database may store a plurality of notification information corresponding to a plurality of notifications generated from a plurality of applications. The notification database can store a plurality of notification information in the form of a predetermined data structure. For example, notification information may include notification transmission information and notification reception information. The notification database is data that has the notification ID as a key value, and the application ID (Identification) corresponding to the notification ID, sender ID, recipient ID, notification type, notification message data, and notification transmission time as attribute values. Notification transmission information can be stored in the form of a structure. In addition, the notification database provides notification reception information in the form of a data structure that has notification ID and recipient ID as key values, and whether notifications corresponding to the notification ID have been read, whether notifications have been deleted, notification read time, and notification deletion time as attribute values. You can save it.

In step S330, the computing device 100 may identify the first user who will receive the first notification based on the first notification information. For example, the computing device 100 may identify the first user corresponding to the first recipient ID based on the first recipient ID included in the first notification information.

In step S340, the computing device 100 may transmit a first message notifying that the first notification has been generated to the first user terminal corresponding to the first user. For example, the first message may be a WebSocket message transmitted from the computing device 100 to the first user terminal through the WebSocket server. For example, when the first user terminal receives the first message, it may be displayed on the notification application of the first user terminal that the first notification has arrived. In one embodiment, the notification application may be an application that provides a service for transmitting to recipients a plurality of notifications generated from a plurality of applications mapped to an application platform. Through this, it is possible to achieve the technical effect of allowing the user to check multiple notifications generated from multiple applications at once through the notification application.

In one embodiment, an application platform may be a service environment that can execute multiple applications provided on a web browser. A user can access an application platform provided on a web browser through a user terminal and run multiple web applications. Additionally, an application platform may be a service environment in which users can develop and build applications. Users can develop applications that can run on the application platform. In one embodiment, the first application may be a web application running on an application platform. In one embodiment, mapping an application onto an application platform may mean including the application in an application platform that a user accesses through a user terminal. The user terminal can select an application to be executed on the application platform from among a plurality of applications.

In one embodiment, the first application may be a web application. The first application may be executed in an iframe corresponding to a web page. In one embodiment, an iframe may refer to a sub-web page included within another web page. For example, an iframe can be an HTML page. In one embodiment, the computing device 100 has first application information, an application ID corresponding to the first application as a key value, and an iframe ID corresponding to an iframe in which the first application is executed. It can be stored in the form of a data structure with attribute (value) values. In another embodiment, the computing device 100 has an application ID corresponding to the first application as an external storage as a key value, and stores the iframe ID corresponding to the iframe in which the first application is executed as an attribute ( The first application information in the form of a data structure with a value (value) can be transmitted. When the user terminal accesses the application platform on a web browser, the computing device 100 may determine an iframe in which the first application will be displayed based on the iframe ID corresponding to the attribute value of the first application ID. The user terminal may receive an application platform where the first application is displayed in the determined iframe.

In one embodiment, the computing device 100 obtains first notification information from a notification DB, and sends a first notification including the contents of the first notification as well as a first message notifying the first user that the first notification has occurred. Data can be transmitted. The first user can check the contents of the first notification based on the first notification data.

In one embodiment, the notification DB may store the first notification information in the form of a predetermined data structure based on the first point in time when the first notification occurred. For example, the notification DB can store a queue corresponding to the recipient. In one embodiment, the first notification reception information included in the first notification information may be stored in a queue corresponding to the first recipient based on the time order in which the first notification is generated. In another embodiment, the first notification reception information corresponds to the first recipient when the first recipient corresponding to the first recipient ID included in the first notification information reads the first notification or deletes the first notification. It can be stored in a queue. The first notification information may be stored in a queue according to the time order in which the first notification was generated.

In one embodiment, when a notification is transmitted from a plurality of applications to a first recipient, a queue corresponding to the first recipient is used to store a plurality of notification information generated from a plurality of applications according to the time order in which each notification was generated. It can represent a structure. For example, if the first recipient is the recipient of the first notification and the second notification from the first application and the second application, the queue corresponding to the first recipient is the first time when the first notification is generated and the second notification is generated. Based on the generated second time point, the first notification reception information and the second notification reception information may be stored in the order of the time when the notification was generated.

In one embodiment, the first user terminal may obtain first notification information from the notification DB based on the first message. For example, the first message may include an address in the notification DB where the first notification information is stored. The first user terminal corresponding to the first user may obtain the first notification information on a web browser by accessing an address in the notification DB where the first notification information is stored.

In one embodiment, the computing device 100 may obtain a plurality of notification information generated from a plurality of applications to be transmitted to the first user. For example, a notification for the first user may be generated in each of the first application and the second application. The computing device 100 may obtain second notification information regarding the second notification from the second application. The computing device 100 may store the second notification information in the notification DB. The computing device 100 may identify the first user terminal to receive the second notification based on the second notification information. The computing device 100 may transmit a second message notifying that a second notification has been generated to the first user terminal. The notification DB may store the second notification information in the form of a predetermined data structure based on the second time point when the second notification is generated. The first user terminal may obtain second notification information from the notification DB based on the second message.

In one embodiment, the computing device 100 may identify a plurality of users including the first user who will receive the first notification, based on the first notification information. For example, the first recipient ID included in the first notification transmission information may include a plurality of user IDs corresponding to the plurality of users included in the room corresponding to the group chat room.

In one embodiment, a room may refer to a service environment corresponding to a group chat room in which messages can be sent and received on at least one application. For example, a room may refer to a service environment provided on a web browser. A plurality of users who are group members included in a room can send and receive messages with the same group members on at least one application mapped to the room through the room.

In one embodiment, the computing device 100 may transmit a first message notifying that a first notification has been generated to a user terminal corresponding to each of a plurality of users. The user terminal corresponding to each of the plurality of users may obtain first notification information from the notification DB based on the first message. Group members of a room can send and receive messages on at least one web application mapped to the room through the room provided by a web browser. In one embodiment, a group chat room may be a service environment configured within an application in which multiple users become group members and can transmit messages to multiple users at once. A user can create a room by selecting a plurality of users through the user terminal, or participate in a pre-created room.

In one embodiment, when the first recipient ID includes a plurality of user IDs, the first notification information may include one first notification transmission information and a plurality of first notification reception information. A plurality of pieces of first notification reception information may each correspond to a plurality of users. The notification database may store the first notification information in the form of a data structure that uses one first notification transmission information as upper data and a plurality of first notification reception information as lower data. In one embodiment, a plurality of notification information generated from a plurality of applications may be stored in a notification list with notification transmission information as upper data and notification reception information as lower data, based on the time order in which they were generated. Notification information may be added to the notification list based on the time order in which the notification information was generated.

In one embodiment, the first application may be mapped to an application platform corresponding to the first user terminal. The first notification type may include a mention type, schedule type, and system type. Notifications of a mention type and notifications of a certain type may be generated from a messenger application. For example, a mention-type notification may be a notification generated when another user mentions the first user in a message or article on a messenger application. For example, a schedule type of notification may be a notification that occurs when another user creates a schedule that includes the first user on a messenger application. Notifications of system type can be generated from the application platform. For example, a system type notification may be a notification for application management sent by multiple applications mapped to an application platform to users using the application. System type notifications may include notifications such as regular application maintenance.

In one embodiment, the first application may be mapped to an application platform corresponding to the first user terminal. The first user terminal may obtain the first notification information through a notification application mapped to the application platform. For example, a notification application may be mapped to an application platform corresponding to the first user. As another example, a notification application is an application provided by default in an application platform and may be an application that can be used regardless of whether it is mapped to an application platform.

In one embodiment, an application platform may be mapped with a first application and a second application. The first application and the second application are based on a preset interaction type between the first application and the second application, and the first data generated by the first application and the second data generated by the second application are connected to the first application on the application platform. The application and the second application may interact in a shared manner.

In one embodiment, the preset interaction type may be set based on application developer information, the data type of data generated in the application, and the category of the application. In one embodiment, data types may include personal information data, weather data, calendar data, message data, and game data. For example, personal information data may refer to user information or information for identifying the user that is additionally input in each of a plurality of applications running on the user terminal. For example, weather data may refer to data containing information about the weather corresponding to a specific date. For example, schedule data may be data containing information about a schedule created by a user in a schedule application, etc. For example, message data may include messages between multiple users transmitted in a messenger application or room. For example, game data may include game character data created by a user in a game application, etc. The user terminal may provide different user information in each of the first application and the second application.

For example, the computing device 100 may determine whether the first application and the second application are applications developed by the same application developer, based on application developer information. If the first application and the second application are developed by the same developer, interaction between the first application and the second application may be set by the developer in the development stage. For example, when the first application and the second application are in the game category, the user's game character data created on the first application may be shared with the second application. A user can use the same game character in the first application and the second application by sharing game character data between the first application and the second application.

For example, when the first application is a schedule application and the second application is a messenger application, the preset interaction type between the first application and the second application may be a schedule sharing type. For example, when the user terminal adds a schedule on the first application, the data type of the first data generated in the first application may be schedule data. First data generated in the first application may be shared with the second application. For example, a message related to the schedule may be transmitted on the second application to another user who is set as a schedule participant in the schedule data. The data type of the second data generated by the second application may be message data. When a user participating in a schedule on the second application transmits a comment related to the schedule, the second application may transmit message data related to the comment to the first application. The first application can map the schedule to the comment.

For example, if the first application is a weather application and the second application is a messenger application, the preset interaction type between the first application and the second application may be a weather sharing type. For example, the data type of the first data generated in the first application may be weather data. The data type of the second data generated by the second application may be message data. First data generated in the first application may be shared with the second application. For example, based on the first user's click/touch input, a message related to the weather may be transmitted to group members of a room containing the first user on the second application. For another example, when bad weather is expected, such as cloudy weather, rainy weather, typhoon weather, or snowy weather, a warning notification related to the weather may be generated on the second application.

For example, if the first application is a weather application and the second application is a schedule application, the preset interaction type between the first application and the second application may be a weather-schedule mapping type. For example, the data type of the first data generated in the first application may be weather data. First data generated in the first application may be shared with the second application. For example, the data type of the second data generated in the second application may be constant data. The second data generated by the second application may be shared with the first application. For example, when the second data is shared with the first application, the first application can obtain the dates on which the schedule exists. The first application may share weather data corresponding to dates for which a schedule exists with the second application. For example, if a schedule exists on a day when bad weather is expected, such as cloudy weather, rainy weather, typhoon weather, or snowy weather, a warning notification related to the weather can be generated in the second application.

For example, if the first application and the second application are game applications produced by the same developer, the preset interaction type between the first application and the second application may be a game type. The data type of the first data generated in the first application and the second data generated in the second application may be game data. The first application and the second application can share each other's game data. For example, game data for a first game character in a first application and game data for a second game character in a second application may be shared. The user can play the second game character in the first application and the first game character in the second application.

In one embodiment, the computing device 100 uses a pre-trained artificial intelligence-based application recommendation model to select an application from user information corresponding to the user, first application information, and second application information corresponding to the second application. Multiple application information corresponding to multiple applications to be mapped to the platform can be obtained. In one embodiment, the pre-trained artificial intelligence-based application recommendation model is a plurality of information to be mapped to the application platform corresponding to the user terminal from the user's age, gender, occupation, and application category of the application mapped to the user terminal included in the user information. It can correspond to an artificial intelligence-based model that has been pre-trained to determine applications. For example, an application recommendation model can be learned through learning data on a preferred application list for applications preferred by user's age, gender, and occupation. Such learning data may include a learning dataset in which user identification information and application information preferred by the user are labeled as correct answer data. Additionally, the application recommendation model may be learned through learning data on a preferred application list for applications preferred by users among applications included in the same or similar categories as the application category. For example, a pre-trained application recommendation model may be operated to receive user identification information (age, gender, education, address, and/or occupation) and output a recommended application corresponding to the user identification information. For example, the application recommendation model includes a feature extractor that outputs user identification information as an N-dimensional feature (N is a natural number), and a classifier that receives the output of the feature extraction model and outputs a classification result of the feature. It can be composed of: For example, features corresponding to each of a plurality of applications may be pre-stored. Based on comparison between pre-stored features and the feature corresponding to the user identification information, recommended application information corresponding to the user identification information may be generated. For example, a feature corresponding to an application may correspond to a dimension composed of a plurality of factors for identifying the type of application.

In one embodiment, the computing device 100 may transmit a plurality of application information obtained from an application recommendation model to the user terminal. The user terminal may receive a plurality of application information obtained from the application recommendation model from the computing device 100 and select at least one application to be mapped to the application platform among the plurality of applications received. The computing device 100 may receive a mapping request for at least one application to be mapped to the application platform from the user terminal. The computing device 100 may obtain at least one application information corresponding to at least one application. The computing device 100 may map at least one application to an application platform. For example, the computing device 100 may receive at least one application information stored in external storage based on a mapping request for at least one application.

In one embodiment, the computing device 100 may obtain a plurality of application information corresponding to a plurality of applications that have a preset interaction type with the first application. For example, a list of applications with preset interaction types for each application can be stored in an external storage. The computing device 100 may obtain a list of first applications in which the first application and a preset interaction type exist from the storage. Based on the first application list, the computing device 100 may obtain a plurality of application information corresponding to a plurality of applications having a preset interaction type with the first application. The computing device 100 may transmit a plurality of application information to the user terminal. The computing device 100 may receive a mapping request for at least one application to be mapped to the application platform from the user terminal. The computing device 100 may obtain at least one application information corresponding to at least one application. The computing device 100 may map at least one application to an application platform.

FIG. 4 is a diagram illustrating a process in which a user obtains notification information from a plurality of applications according to an embodiment of the present disclosure.

In step S401, the first application 401 and the second application 402 may transmit first notification information regarding the first notification and second notification information regarding the second notification to the computing device 100. The first notification information and the second notification information may be notification information to be transmitted to the first user.

In step S402, the computing device 100 may store the received first notification information and second notification information in the notification DB 403. Additionally, in step S403, the computing device 100 may query user information in the user information DB 404. The user information DB 404 may correspond to a database that stores user information including web socket server information, room information, and user ID corresponding to each of a plurality of user terminals using the application platform. Room information may include a room ID. The computing device 100 may obtain first user information about the first user from the user information DB 404 based on the first notification information and the second notification information. The computing device 100 may identify the first user who will receive the first notification and the second notification based on the first user information.

In step S404, the computing device 100 may transmit a first message notifying that a first notification has been generated to the first user terminal 406 corresponding to the first user. For example, the computing device 100 may transmit a first message, which is a notification generation message, to the first user terminal 406 through the websocket server 405.

In step S405, the first user terminal 406 may obtain first notification information from the notification DB 403 based on the first message. For example, the first message may include an address in the notification DB 403 where the first notification information is stored. The first user terminal 406 can obtain the first notification information by accessing the address in the notification DB 403 on a web browser through the World Wide Web. The first notification information may include notification data related to the first notification.

Figure 5 is a brief, general schematic diagram of an example computing environment in which embodiments of the present disclosure may be implemented.

Although the disclosure has been described above as being capable of being implemented generally by a computing device, those skilled in the art will understand that the disclosure can be implemented in combination with computer-executable instructions or other program modules that can be executed on at least one computer, or as a combination of hardware and software. You will know very well that it can be done.

Typically, program modules include routines, programs, components, data structures, etc. that perform specific tasks or implement specific abstract data types. Additionally, those skilled in the art will understand that the methods of the present disclosure are applicable to single-processor or multiprocessor computer systems, minicomputers, mainframe computers, as well as personal computers, handheld computing devices, microprocessor-based or programmable consumer electronics, etc. It will be appreciated that each of these may be implemented in other computer system configurations, including those capable of operating in conjunction with at least one associated device.

The described embodiments of the disclosure can also be practiced in distributed computing environments where certain tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote memory storage devices.

Computers typically include a variety of computer-readable media. Computer-readable media can be any medium that can be accessed by a computer, and such computer-readable media includes volatile and non-volatile media, transitory and non-transitory media, removable and non-transitory media. Includes removable media. By way of example, and not limitation, computer-readable media may include computer-readable storage media and computer-readable transmission media. Computer-readable storage media refers to volatile and non-volatile media, transient and non-transitory media, removable and non-removable, implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Includes media. Computer readable storage media may include RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital video disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage. This includes, but is not limited to, a device, or any other medium that can be accessed by a computer and used to store desired information.

A computer-readable transmission medium typically implements computer-readable instructions, data structures, program modules, or other data on a modulated data signal, such as a carrier wave or other transport mechanism. Includes all information delivery media. The term modulated data signal refers to a signal in which at least one of the characteristics of the signal is set or changed to encode information within the signal. By way of example, and not limitation, computer-readable transmission media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared, and other wireless media. Combinations of any of the above are also intended to be included within the scope of computer-readable transmission media.

An example environment implementing various aspects of the present disclosure is shown, including computer 1102, which includes processing unit 1104, system memory 1106, and system bus 1108. System bus 1108 couples system components, including but not limited to system memory 1106, to processing unit 1104. Processing unit 1104 may be any of a variety of commercially available processors. Dual processors and other multiprocessor architectures may also be used as processing unit 1104.

System bus 1108 may be any of several types of bus structures that may further be interconnected to a memory bus, peripheral bus, and local bus using any of a variety of commercial bus architectures. System memory 1106 includes read only memory (ROM) 1110 and random access memory (RAM) 1112. The basic input/output system (BIOS) is stored in non-volatile memory 1110, such as ROM, EPROM, and EEPROM, and is a basic input/output system that helps transfer information between components within the computer 1102, such as during startup. Contains routines. RAM 1112 may also include high-speed RAM, such as static RAM, for caching data.

Computer 1102 may also include an internal hard disk drive (HDD) 1114 (e.g., EIDE, SATA)—the internal hard disk drive 1114 may also be configured for external use within a suitable chassis (not shown). Yes - a magnetic floppy disk drive (FDD) 1116 (e.g., for reading from or writing to a removable diskette 1118), and an optical disk drive 1120 (e.g., a CD-ROM for reading the disk 1122 or reading from or writing to other high-capacity optical media such as DVDs). Hard disk drive 1114, magnetic disk drive 1116, and optical disk drive 1120 are connected to system bus 1108 by hard disk drive interface 1124, magnetic disk drive interface 1126, and optical drive interface 1128, respectively. ) can be connected to. The interface 1124 for implementing an external drive includes at least one or both of Universal Serial Bus (USB) and IEEE 1394 interface technologies.

These drives and their associated computer-readable media provide non-volatile storage of data, data structures, computer-executable instructions, and the like. For computer 1102, drive and media correspond to storing any data in a suitable digital format. Although the description of computer-readable media above refers to removable optical media such as HDDs, removable magnetic disks, and CDs or DVDs, those skilled in the art will also recognize removable optical media such as zip drives, magnetic cassettes, flash memory cards, cartridges, etc. It will be appreciated that other types of computer-readable media may also be used in the example operating environment, and that any such media may contain computer-executable instructions for performing the methods of the present disclosure.

A number of program modules may be stored in the drive and RAM 1112, including an operating system 1130, at least one application program 1132, other program modules 1134, and program data 1136. All or portions of an operating system, application, module, or data may also be cached in RAM 1112. It will be appreciated that the present disclosure may be implemented on various commercially available operating systems or combinations of operating systems.

A user may input commands and information into the computer 1102 through at least one wired/wireless input device, for example, a keyboard 1138 and a pointing device such as a mouse 1140. Other input devices (not shown) may include microphones, IR remote controls, joysticks, game pads, stylus pens, touch screens, etc. These and other input devices are connected to the processing unit 1104 through an input device interface 1142, which is often connected to the system bus 1108, but may also include a parallel port, an IEEE 1394 serial port, a game port, a USB port, an IR interface, It can be connected by other interfaces, etc.

A monitor 1144 or other type of display device is also connected to system bus 1108 through an interface, such as a video adapter 1146. In addition to monitor 1144, computers typically include other peripheral output devices (not shown) such as speakers, printers, etc.

Computer 1102 may operate in a networked environment using a logical connection to at least one remote computer, such as remote computer(s) 1148, through wired or wireless communications. Remote computer(s) 1148 may be a workstation, computing device computer, router, personal computer, portable computer, microprocessor-based entertainment device, peer device, or other conventional network node, and is generally connected to computer 1102. For simplicity, only memory storage device 1150 is shown, although it includes many or all of the components described. The logical connections depicted include wired/wireless connections to a local area network (LAN) 1152 or a larger network, such as a wide area network (WAN) 1154. These LAN and WAN networking environments are common in offices and companies and facilitate enterprise-wide computer networks, such as intranets, all of which can be connected to a worldwide computer network, such as the Internet.

When used in a LAN networking environment, computer 1102 is connected to local network 1152 through a wired or wireless communications network interface or adapter 1156. Adapter 1156 may facilitate wired or wireless communication to LAN 1152, which also includes a wireless access point installed thereon for communicating with wireless adapter 1156. When used in a WAN networking environment, the computer 1102 may include a modem 1158 or be connected to a communicating computing device on the WAN 1154 or to establish communications over the WAN 1154, such as over the Internet. Have other means. Modem 1158, which may be internal or external and a wired or wireless device, is coupled to system bus 1108 via serial port interface 1142. In a networked environment, program modules described for computer 1102, or portions thereof, may be stored in remote memory/storage device 1150. It will be appreciated that the network connections shown are exemplary and that other means of establishing a communications link between computers may be used.

Computer 1102 may be any wireless device or object deployed and operating in wireless communications, such as a printer, scanner, desktop or portable computer, portable data assistant (PDA), communications satellite, or any wireless detectable tag. Perform actions that communicate with equipment, locations, and telephones. This includes at least Wi-Fi and Bluetooth wireless technologies. Accordingly, communication may be a predefined structure as in a conventional network or may simply be ad hoc communication between at least three devices.

Wi-Fi (Wireless Fidelity) enables connection to the Internet, etc. without wires. Wi-Fi is a wireless technology, like cell phones, that allows these devices, such as computers, to send and receive data indoors and outdoors, anywhere within the coverage area of a cell tower. Wi-Fi networks use wireless technology called IEEE 802.11 (a, b, g, etc.) to provide secure, reliable, and high-speed wireless connections. Wi-Fi can be used to connect computers to each other, to the Internet, and to wired networks (using IEEE 802.3 or Ethernet). Wi-Fi networks can operate in the unlicensed 2.4 and 5 GHz wireless bands, for example, at data rates of 11 Mbps (802.11a) or 54 Mbps (802.11b), or in products that include both bands (dual band). .

Those skilled in the art will understand that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, values, symbols and chips that may be referenced in the above description include voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields. or particles, or any combination thereof.

Those skilled in the art will understand that various illustrative logical blocks, modules, processors, means, circuits and algorithm steps described in connection with the embodiments disclosed herein may be used in electronic hardware, (for convenience) It will be understood that it may be implemented by various forms of program or design code (referred to herein as software) or a combination of both. To clearly illustrate this interoperability of hardware and software, various illustrative components, blocks, modules, circuits and steps have been described above generally with respect to their functionality. Whether this functionality is implemented as hardware or software depends on the specific application and design constraints imposed on the overall system. A person skilled in the art of this disclosure may implement the described functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of this disclosure.

The various embodiments presented herein may be implemented as a method, device, or article of manufacture using standard programming or engineering techniques. The term article of manufacture includes a computer program, carrier, or media accessible from any computer-readable storage device. For example, computer-readable storage media include magnetic storage devices (e.g., hard disks, floppy disks, magnetic strips, etc.), optical disks (e.g., CDs, DVDs, etc.), smart cards, and flash. Includes, but is not limited to, memory devices (e.g., EEPROM, cards, sticks, key drives, etc.). Additionally, the various storage media presented herein include at least one device or other machine-readable medium for storing information.

It is to be understood that the specific order or hierarchy of steps in the processes presented is an example of illustrative approaches. It is to be understood that the specific order or hierarchy of steps in processes may be rearranged within the scope of the present disclosure, based on design priorities. The appended method claims present elements of the various steps in a sample order but are not meant to be limited to the particular order or hierarchy presented.

The description of the presented embodiments is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments without departing from the scope of the disclosure. Thus, the present disclosure is not limited to the embodiments presented herein but is to be interpreted in the broadest scope consistent with the principles and novel features presented herein.

Claims (10)

In a method of transmitting notification information to a user, performed by a computing device,
Obtaining first notification information regarding the first notification from the first application;
Storing the first notification information in a notification database (DataBase, DB);
Based on the first notification information, identifying a first user to receive the first notification; and
Transmitting a first message notifying that the first notification has been generated to a first user terminal corresponding to the first user;
Includes,
The notification DB stores the first notification information in the form of a predetermined data structure based on the first point in time when the first notification occurred,
The first user terminal obtains the first notification information from the notification DB based on the first message,
The first notification information includes first notification transmission information and first notification reception information,
The first notification transmission information has the first notification ID as a key value, and a first application ID (Identification) corresponding to the first notification ID, a first sender ID, a first recipient ID, and a first notification type. , It is a form of a data structure that has the first notification message data and the first notification transmission time as attribute values, and
The first notification reception information has the first notification ID and the first recipient ID as key values, and includes whether the first notification corresponding to the first notification ID has been read, whether the first notification has been deleted, a first notification reading time, and In the form of a data structure that has the first notification deletion time as an attribute value,
method.
According to claim 1,
Obtaining second notification information regarding the second notification from the second application;
storing the second notification information in a notification DB;
Based on the second notification information, identifying the first user terminal to receive the second notification; and
Transmitting a second message notifying that the second notification has occurred to the first user terminal;
It further includes, and
The notification DB stores the second notification information in the form of the predetermined data structure based on the second time point when the second notification is generated,
The first user terminal obtains the second notification information from the notification DB based on the second message,
method.
delete According to claim 1,
The step of transmitting the first message is,
Based on the first notification information, identifying a plurality of users including the first user who will receive the first notification; and
Transmitting the first message notifying that the first notification has been generated to a user terminal corresponding to each of the plurality of users;
Contains and
The first recipient ID includes a plurality of user IDs corresponding to the plurality of users included in a room corresponding to a group chat room, and
The user terminal corresponding to each of the plurality of users obtains the first notification information from the notification DB based on the first message,
method.
According to claim 1,
The first notification reception information is,
When the first user reads the first notification or deletes the first notification, it is stored in a queue corresponding to the first user, and
Notifications are stored in the queue according to the time order in which they were generated,
method.
According to claim 1,
The first application is mapped to an application platform corresponding to the first user terminal,
The first notification type includes a mention type, a schedule type, and a system type,
The notification of the mentioned type and the notification of the certain type are generated from a messenger application, and
Notifications of the system type are generated from the application platform,
method.
delete In a method of transmitting notification information to a user, performed by a computing device,
Obtaining first notification information regarding the first notification from the first application;
Storing the first notification information in a notification database (DataBase, DB);
Based on the first notification information, identifying a first user to receive the first notification; and
Transmitting a first message notifying that the first notification has been generated to a first user terminal corresponding to the first user;
Includes,
The notification DB stores the first notification information in the form of a predetermined data structure based on the first point in time when the first notification occurred,
The first application is mapped to an application platform corresponding to the first user terminal,
Based on the first message, the first user terminal obtains the first notification information from the notification DB through a notification application mapped to the application platform,
The application platform is mapped with the first application and the second application,
The first application and the second application, based on a preset interaction type between the first application and the second application, first data generated by the first application and the second application on the application platform. interact in such a way that the generated second data is shared with each of the first application and the second application,
The preset interaction type is set based on application developer information, the data type of data generated in the application, and the category of the application, and
The data types include personal information data, weather data, schedule data, message data, and game data.
method.
A computing device for transmitting notification information to a user, comprising:
at least one processor; and
Memory;
Includes,
The at least one processor,
Obtaining first notification information regarding the first notification from the first application,
Store the first notification information in a notification database (DataBase, DB),
Based on the first notification information, identify a first user who will receive the first notification, and
Transmitting a first message notifying that the first notification has occurred to a first user terminal corresponding to the first user,
The notification DB stores the first notification information in the form of a predetermined data structure based on the first time point when the first notification occurred,
The first user terminal obtains the first notification information from the notification DB based on the first message,
The first notification information includes first notification transmission information and first notification reception information,
The first notification transmission information has the first notification ID as a key value, and a first application ID (Identification) corresponding to the first notification ID, a first sender ID, a first recipient ID, and a first notification type. , It is a form of a data structure that has the first notification message data and the first notification transmission time as attribute values, and
The first notification reception information has the first notification ID and the first recipient ID as key values, and includes whether the first notification corresponding to the first notification ID has been read, whether the first notification has been deleted, a first notification reading time, and In the form of a data structure that has the first notification deletion time as an attribute value,
Computing device.
A computer program stored in a computer-readable storage medium, wherein the computer program, when executed by one or more processors, causes the one or more processors to perform operations for transmitting notification information to a user, the operations comprising:
Obtaining first notification information regarding the first notification from the first application;
An operation of storing the first notification information in a notification database (DataBase, DB);
Identifying a first user to receive the first notification based on the first notification information; and
Transmitting a first message notifying that the first notification has been generated to a first user terminal corresponding to the first user;
Includes,
The notification DB stores the first notification information in the form of a predetermined data structure based on the first time point when the first notification occurred,
The first user terminal obtains the first notification information from the notification DB based on the first message,
The first notification information includes first notification transmission information and first notification reception information,
The first notification transmission information has the first notification ID as a key value, and a first application ID (Identification) corresponding to the first notification ID, a first sender ID, a first recipient ID, and a first notification type. , It is a form of a data structure that has the first notification message data and the first notification transmission time as attribute values, and
The first notification reception information has the first notification ID and the first recipient ID as key values, and includes whether the first notification corresponding to the first notification ID has been read, whether the first notification has been deleted, a first notification reading time, and In the form of a data structure that has the first notification deletion time as an attribute value,
A computer program stored on a computer-readable storage medium.

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