KR20200117474A - Apparatus for Intellectual Learning Service and Driving Method Thereof - Google Patents

Abstract

The present invention relates to an apparatus for an intellectual learning service and a driving method thereof. According to an embodiment of the present invention, an apparatus for an intellectual learning service may comprise: a storage unit which stores lecture data of an instructor and matches and stores search words for automatic response search when storing the lecture data; and a control unit which automatically transmits (pre)stored lecture data to a learner terminal device based on query contents of a learning query and a stored search word when there is the learning query based on an interactive messenger from the learner terminal device, and transmits the learning query to an instructor terminal device of the instructor when there is no lecture data to provide.

Description

Intelligent Learning Service and Driving Method {Apparatus for Intellectual Learning Service and Driving Method Thereof}

The present invention relates to an intelligent learning service device and a method of driving the device, and more particularly, when students perform pre-study or review at a university, an answer to a query or data is provided through an interactive messenger such as an intelligent conversation robot. It relates to an intelligent learning service device that automatically receives and solves learning disabilities, and a driving method of the device.

Electronic learning is called by various names such as e-learning or electronic education, but it is the same in that education can be performed electronically. E-learning is a system that enables customized learning at any level, anytime, anywhere, anyone, using information and communication technology. E-learning has the same meaning as ICT-based education as an education where learning space and learning experience can be expanded and learner initiative can be reinforced compared to the traditional educational field. However, with the development of information and communication technology, education using ICT can be understood in an expanded and developed form in terms of learning environments, methods, and contents.

However, despite the widespread use of e-learning, for example, many university students are in a state of being unable to directly speak with the professor in real time if they have questions or questions to be asked during the preparation or review process. There are problems with learning difficulties, and when using e-mails or bulletin boards, there are many inconveniences such as having to check in real time whether there is a professor's answer.

Korean Patent Application Publication No. 10-2018-0003417 (2018.01.09.) Korean Registered Patent Publication No. 10-1929800 (2018.12.11.)

An embodiment of the present invention is an intelligent learning service device for solving learning disabilities by automatically receiving an answer or data to a query through an interactive messenger such as an intelligent conversation robot when students perform pre-study or review in a university, and the like. An object thereof is to provide a method of driving a device.

The intelligent learning service device according to an embodiment of the present invention includes a storage unit that stores lecture data of an instructor, matches and stores a search word for automatic response search when storing the lecture data, and an interactive messenger-based device from a learner terminal device. When there is a learning query, the stored lecture data is automatically transmitted to the learner terminal device based on the query content of the learning query and the stored search word, and when there is no lecture data to be provided, it is sent to the instructor's terminal device. And a control unit that transmits the learning query.

The storage unit stores answer contents and lecture data for responding to the query contents as the lecture data, and the control unit selects and provides one of the stored answer contents and the lecture data based on the query contents. I can.

The controller may inquire whether or not to directly answer the content of the query while transmitting the learning query to the instructor's terminal device, and may cope with the situation of the learning query according to a response result of the inquiry.

If there is no answer for a specified time after the inquiry, the control unit may notify the learner terminal device to respond later.

The control unit may transmit the extracted data obtained by extracting a part related to the content of the query from the lecture data of the instructor as the lecture data.

In addition, the driving method of the intelligent learning service device according to an embodiment of the present invention is a driving method of an intelligent learning service device including a storage unit and a control unit, which stores lecture data of an instructor, and automatically responds when the lecture data is stored. Matching a search word for a search and storing it in the storage unit, and when the control unit receives a learning query based on an interactive messenger from a learner terminal device, based on the query content of the learning query and the stored search word And automatically transmitting the stored lecture data to the learner terminal device, and transmitting the learning query to the instructor's instructor terminal device when there is no lecture data to be provided.

The storing step includes storing answer contents and lecture data for answering the query contents as the lecture data, and the transmitting step includes one of the stored answer contents and the lecture data based on the query contents. You can choose to provide it.

The driving method may include inquiring whether to directly answer the query content while transmitting the learning query to the instructor terminal device, and coping with the situation of the learning query according to a response result to the inquiry.

The driving method may include, if there is no answer for a specified time after the inquiry, notifying the learner terminal device to answer later.

The driving method may include transmitting, as the lecture data, extract data obtained by extracting a portion related to the content of the query from the lecture data of the instructor.

According to an embodiment of the present invention, by being able to provide an impromptu answer to inquiries or provide related materials in the process of pre-study or review by students, learning efficiency will increase, and it will be helpful for students' learning ability. .

1 is a diagram showing an intelligent learning service system according to an embodiment of the present invention;
FIG. 2 is a diagram illustrating an example screen on the learner terminal device of FIG. 1;
3 is a block diagram illustrating a detailed structure of the intelligent learning service device of FIG. 1, and
4 is a flowchart illustrating a driving process of the intelligent learning service device of FIG. 1.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the drawings.

1 is a diagram illustrating an intelligent learning service system according to an embodiment of the present invention, and FIG. 2 is a diagram illustrating a screen on a learner terminal device of FIG. 1.

As shown in Fig. 1, the intelligent learning service system 90 according to an embodiment of the present invention is a learning service system using an intelligent conversational robot such as a chatbot, and includes a teacher terminal device 100 and a learner terminal device. (110), the communication network 120, and includes some or all of the intelligent learning service device 130.

Here, "including some or all" means that some components such as the communication network 120 are omitted so that the instructor terminal device 100 or the learner terminal device 110 communicates directly with the intelligent learning service device 130 (for example, : P2P communication) or a part or all of the intelligent learning service device 130 is integrated into a network device (for example, a wireless switching device, etc.) in the communication network 120 to be configured. Explain that it is all inclusive to help you understand it.

The instructor terminal device 100 includes a desktop computer, a laptop computer, a tablet PC, a smart phone, and even a smart TV, and may further include an artificial intelligence (AI) speaker as a peripheral device thereof. The instructor terminal device 100 is a terminal device used by a professor, such as a professor who conducts a lecture at a university, etc., and the instructor responds to an expected question or question when students prepare and review their class through the terminal device. Provides information, or data, about answers or learning materials. For example, if there is a lecture recording for a lecture in a specific subject or a lecture note such as a power point (PPT), the lecture material is provided to the intelligent learning service device 130 and the user is provided with an intelligent conversation robot-based search. A search word is provided to enable the provided lecture data and answers to be provided as lecture data. Of course, the search word may be a subject, subject matter, content, or keyword for the lecture. Such a search keyword may be input in various ways according to the shape of a user interface (UI) window such as a pop-up window. For example, category items such as a first search word and a second search word may be classified and entered in order.

When the instructor provides the lecture data in the instructor terminal device 100, the intelligent learning service device 130 selects the expected keyword or search word based on a specific search word, that is, a first keyword, or by partially analyzing the contents of the related lecture data. You can give it to your instructor and then let him choose. As such, the keyword presented to the instructor as an example collects data through various paths in the intelligent learning service device 130 or performs an operation such as deep learning of artificial intelligence (AI) through data accumulated based on the corresponding service. Thus, it may be possible to create and present a keyword as an example. In this way, the instructor can directly input a keyword, that is, a search word, through the instructor terminal device 100, but can provide information on various keywords, that is, an expected question, among the automatically suggested keywords. If a keyword usually means a compound noun of a word such as a common noun, the search word may be understood as a meaning including a sentence.

In general, lecture materials for instructors will consist of 14 weeks to 15 weeks per semester, and keywords can be provided based on the contents of the lecture for each week, so there will be no difficulty in providing keywords for keywords or expected questions. .

In addition, if the teacher terminal device 100 cannot provide an answer to a query from the intelligent learning service device 130 or cannot provide related data with respect to the student's question, the intelligent learning service device 130 Receive your inquiry. Accordingly, the instructor can answer questions of students through the instructor terminal device 100.

In this process, for example, the intelligent learning service device 130 may first inquire whether it can directly answer a student's inquiries to the instructor terminal device 100. Therefore, if there is an inquiry as to whether a direct answer is possible, the inquiry can be answered simply in the form of Yes or No. Of course, the instructor may inform you that it is not possible to answer immediately, and may provide an answer to the question later.

Like the teacher terminal device 100, the learner terminal device 110 includes various devices such as a laptop computer, a tablet PC, and a smart phone for using the services of the intelligent learning service device 130. Intelligent conversation robots (eg, chatbots, chatterbots, chatterboxes, conversation agents, etc.) can be implemented on a PC or mobile basis, so it is not a big problem. Therefore, the learner terminal device 110 can use the intelligent conversation robot in two types. For example, it is possible to download and execute it from the learner terminal device 110 in the form of an application (hereinafter, referred to as an app), but click the chatbot messenger icon displayed on the main screen or on the designated screen provided by the intelligent learning service device 130 You can make a query. In the embodiment of the present invention, the former case may be more preferable than the latter. In other words, it can be seen as implementing a dedicated chatbot messenger for learning.

After executing the chatbot messenger for learning on the screen of the learner's terminal device 110, the learner executes a chatbot messenger for learning, and when he/she wants to know a question during preparation or review, or the lecture material of a lecturer in charge of the class or a specific content of the lecture material, You can inquire through For example, FIG. 2 shows that a student Gil-dong Hong is provided with lecture materials related to his/her request through a messenger. The learner terminal device 110 receives answers based on a chatbot, or more precisely, an intelligent conversation robot, and can receive lecture data, but if the chatbot cannot provide a service, that is, an answer to a query, it contacts the instructor Answers related to the instructor's response can be provided. Here, the answer related to the response can be transmitted to the learner as it is, but indirectly, for example, when asked whether an immediate answer is possible, and receiving that it is impossible, it includes transmitting the content that the current answer is impossible.

In other words, when the intelligent learning service device 130 cannot provide an answer to a learner's query or lecture data, the learner's terminal device 110 transmits the learner's query content to the instructor's terminal device 100. At this time, you are asking if you can respond directly. If the instructor gives a response that it is difficult right now, based on the response, the intelligent learning service device 130, more precisely, the chatbot sends a message such as "The professor is currently in a state that cannot provide an answer." Is to do. In this way, a learner using the learner terminal device 110 can receive the help of learning through the chatbot in real time when there is a content to be queried from the instructor during the preparation or review process, and thus can have continuity of learning. Yes, learning efficiency will increase.

For example, a specific student may transmit a message in the form of "Professor, I want to know the scale of the blockchain industry a little" as shown in FIG. 2 using the learner's terminal device 110 during preparation or review. Of course, the student knows that these questions will be handled by the chatbot, but if the professor can receive a message, he can send it as "professor." In this way, when a message is transmitted, the intelligent learning service device 130 of FIG. 1 analyzes the message, and based on the analysis result, the instructor provides matching answer content or lecture data in comparison with the keyword entered in advance. I can. Of course, lecture material can be provided only when a student requests the material as a result of the analysis of the message. In addition, the data provided in the objection process may not be direct data desired by the student as it can be provided by determining the degree of similarity in the intelligent learning service device 130.

In this case, for example, the student and the chatbot continue to have conversations with each other. For example, if a student sends a message in the form of "The data provided now is a little different from the data I am looking for" or "I wanted to know the size of the blockchain market", the chatbot analyzes the message again and makes a query. It will be possible to provide appropriate lecture materials. Of course, lecture materials may be provided in the form of extracts from the entire data. In an embodiment of the present invention, a sentence-based natural language processing technology may be used. Semantic web technology that allows computers to understand information and infer logically, text mining technology that finds useful information from data composed of characters, and context-aware computing technology that grasps the situation and context of the conversation partner can be applied in various ways. .

The communication network 120 includes all wired and wireless communication networks. For example, as the communication network 120, a wired or wireless Internet network may be used or interlocked. Here, the wired network includes an Internet network such as a cable network or a public telephone network (PSTN), and the wireless communication network includes CDMA, WCDMA, GSM, Evolved Packet Core (EPC), Long Term Evolution (LTE), and Wibro networks. It is meant to include. Of course, the communication network 120 according to the embodiment of the present invention is not limited thereto, and may be used as an access network for a next-generation mobile communication system to be implemented in the future, for example, a cloud computing network or a 5G network under a cloud computing environment. For example, when the communication network 120 is a wired communication network, the access point in the communication network 120 can be connected to the switching center of the telephone office, but in the case of a wireless communication network, data is accessed by accessing SGSN or GGSN (Gateway GPRS Support Node) operated by the communication company. Alternatively, data can be processed by accessing various repeaters such as BTS (Base Station Transmission), NodeB, and e-NodeB.

The communication network 120 may include an access point. Here, the access point includes a small base station such as a femto or pico base station that is frequently installed in a building. Here, the femto or pico base station is classified according to the maximum number of the instructor terminal device 100 or the learner terminal device 110 can be connected according to the classification of the small base station. Of course, the access point includes a short-range communication module for performing short-range communication such as Zigbee and Wi-Fi with the instructor terminal device 100 or the learner terminal device 110. The access point may use TCP/IP or Real-Time Streaming Protocol (RTSP) for wireless communication. Here, short-range communication may be performed in various standards such as Bluetooth, Zigbee, infrared, radio frequency (RF) such as ultra high frequency (UHF) and very high frequency (VHF), and ultra wideband communication (UWB) in addition to Wi-Fi. Accordingly, the access point can extract the location of the data packet, designate the best communication path for the extracted location, and deliver the data packet to the next device, for example, the intelligent learning service device 130 along the designated communication path. The access point can share several lines in a general network environment, and includes, for example, a router, a repeater, and a repeater.

The intelligent learning service device 130 provides a learning service based on an intelligent conversational robot according to an embodiment of the present invention. Of course, this intelligent conversational robot-based learning service can be used in a variety of places, but it will be described using universities as an example. For example, an icon representing an interactive robot, for example, a chatbot, may be displayed on the main screen of the university's homepage, which may be executed to make a query. If the intelligent learning service device 130 is a dedicated device such as a server that provides a service based on an intelligent conversation robot, in other words, if it is a messenger provided by a messenger company such as Kaka*Talk, it may be possible through this. Therefore, in the embodiment of the present invention, there will be no particular limitation on what type of service is provided.

In an exemplary embodiment of the present invention, instructors access the intelligent learning service device 130 to provide lecture data and keywords, and so on. For example, when a learner executes a messenger through the learner terminal device 110, a screen for chatting is displayed as shown in FIG. 2. In other words, the message transmission window is created. This can be implemented in the form of an app. In an embodiment of the present invention, a conversation is performed with an intelligent conversational robot through a chat, but a conversation related to learning, and further learning or counseling for further education may be conducted to help learning.

For example, the intelligent learning service device 130 according to an embodiment of the present invention may provide a video or video lecture using a chatbot. The intelligent learning service device 130, for example, as a main server, stores information on academic lectures of professors in each department, and separates and stores frames for each lecture content using a voice file for each lecture. Of course, here, the frame may be a unit for each week such as week 1 or week 2. At this time, each frame setting is produced by allowing the professors to input the subject, subject matter, content, and keywords for their lectures in advance. When students ask a question about learning through a chatbot, a frame of a voice file or video with high similarity, that is, a high similarity, is provided in relation to the related question. At this time, if there is no related video, the intelligent learning service device 130 automatically notifies the content of the learner's query through the chatbot to the instructor terminal device 100 and asks whether or not to directly answer it. If there is no contact from the instructor terminal device 100 for a predetermined period of time, the learner is notified to answer later, and when a contact comes from the instructor terminal device 100, the learner is immediately notified to improve learning ability. All of the above actions indicate that a chatbot, that is, an artificial intelligence (AI) robot, detects all contents or situations by itself and operates according to a specified rule. Of course, the designation rules here include algorithms such as deep learning.

For example, the intelligent learning service device 130 conducts a chat with the learner through an interactive messenger, informs the learner of the objection when a contact comes from the instructor terminal device 100, and allows the learner and the instructor to directly conduct the chat. You can also connect. In other words, chatbots mediate learners and instructors to chat. In this way, the learning service device 130 responds to a learner's query, or provides lecture data, and further allows a direct conversation with the instructor, and the method of monitoring and monitoring the situation may be various. In other words, if the instructor does not answer after receiving a contact from the instructor, a message to continue the conversation with the learner may be transmitted to the instructor's terminal device 100. Or, like a group car*room, learners, chatbots, and instructors can conduct group chats. In other words, chatbots mediate learners and instructors to continue conversations freely. As described above, various methods may be possible with respect to the chatting implementation method, and above all, since it may be designed in various ways according to the intention of the system designer, it will not be specifically limited to any one method in the embodiment of the present invention.

Of course, the intelligent learning service device 130 according to an embodiment of the present invention performs an operation such as providing a keyword when the instructor stores lecture data in the system, and provides keywords by classifying frames from the lecture data. Although, for example, the intelligent learning service device 130 analyzes the contents of a lecture, it may be possible to automatically generate keywords. For example, after analyzing only the major and subtitles, it responds to the learner's request for data based on this. In other words, when a learner requests material, a specific chapter can be extracted and provided based on keywords. In this case, when providing lecture materials in the form of audio files or PPT lecture notes, instructors can reduce the task of classifying frames. That is, the intelligent learning service device 130 performs an editing operation. Of course, it is desirable to provide services within the scope of not infringing on the instructor's copyright, etc.

Further, the intelligent learning service device 130 may not limit the service range to a specific university or academy, as mentioned above, but may extend the range of a nationwide academy or a nationwide university. For example, when a learner uses a service or makes an inquiry, appropriate information is provided together. For example, when a learner enters information on the university, department, or grade that he is currently attending, it analyzes data or keywords of a specific subject or professor based on this, and the chatbot provides an answer to the learner's query based on the analysis result or learns. It is to provide data.

Of course, chatbots are also included in artificial intelligence programs. In other words, it is because it performs the function of self-recognizing conversations of natural persons. It simply implements more chat messenger programs for conversation. Therefore, the intelligent learning service device 130 according to an embodiment of the present invention performs deep learning based on data collected in connection with learners' learning or provided by instructors, and uses a chatbot based on the analysis result. The performance of learning services can be improved. For example, accumulating learner experiences. In other words, if many learners are satisfied with a specific answer to the same question and there is no separate feedback as a result of providing the answer, the probability is increased by weighting the corresponding answer. Through this, it will be possible to increase the satisfaction level of learners' service requests by periodically changing the ranking in the candidate group of answers or learning materials by deep learning.

3 is a block diagram showing a detailed structure of the intelligent learning service device of FIG. 1.

As shown in Figure 3, the intelligent learning service device 130 according to the embodiment of the present invention is a part of the communication interface unit 300, the control unit 310, the intelligent learning processing unit 320 and the storage unit 330 or Includes all.

Here, "including some or all" means that some components such as the storage unit 330 are omitted, or some components such as the intelligent learning processing unit 320 are included in other components such as the control unit 310. It is intended to mean something that can be integrated and configured, and will be described as including all in order to help a sufficient understanding of the invention.

The communication interface unit 300 performs messenger communication such as, for example, a chatbot messenger with the learner terminal device 110 of FIG. 1, and furthermore, the instructor terminal device 100. Here, the messenger means an instant messenger as one of the communication methods on the Internet. In other words, netizens who have installed the same instant messenger program can perform various communication functions from terminal to terminal without connecting to a separate site. You can chat with each other by installing an instant messenger program without signing up for a separate Internet or PC communication service. In addition, since the program itself is small, it can be installed without burden, and there is no additional cost to download it. The operating principle of such a program is to ensure that users registered in the list check their IP addresses and check online status from time to time, thereby securing the basis for operating various services provided. The message can be delivered in three ways: a central network method, a peer-to-peer (P2P) connection method, or a combination of the two.

Accordingly, the communication interface unit 300 according to an embodiment of the present invention may perform communication in a combination of the two according to a specified situation. In other words, the communication interface unit 300 responds to the student's query by itself without the help of the instructor according to the instruction of the control unit 310, and responds by itself through the intelligent dialogue robot, and sends the requested learning data. It can be provided, but when the situation is not handled by itself, the instructor is notified of the query or the content of the query, and intermediaries to provide answers or learning materials. Here, mediation refers to an action that recognizes a situation and responds appropriately, not a relay that simply performs delivery. In this way, the communication interface unit 300 may perform various communication operations under the control of the controller 310.

Of course, the communication interface unit 300 may further perform operations such as modulation/demodulation, encoding/decoding, muxing/demuxing, and scaling for converting the resolution in the process of performing communication. Of course, it is also possible to perform further encryption or decryption operations. When it is determined that the personal information is transmitted, the personal information may be encrypted and transmitted under the control of the controller 310. Of course, when transmitting, the public key may be provided so that the other party can decrypt it.

The control unit 310 is in charge of overall control operations of the communication interface unit 300, the intelligent learning processing unit 320, and the storage unit 330 constituting the intelligent learning service device 130 of FIG. 3. For example, the control unit 310 controls the intelligent learning processing unit 320 to help learners learn through an artificial intelligence program such as an intelligent conversation robot, for example, a chatbot. In other words, it helps learners to solve the difficulties of learning through a one-on-one messenger method when they have a question that they are curious about while performing a preliminary study in order to prepare for a class in a specific subject or reviewing a lecture that has already been made. Of course, difficulties in learning may include career counseling or various counseling related to learning. However, in the embodiment of the present invention, for convenience, only the learning query will be described.

More specifically, when a learner's query is received through the communication interface unit 300, the control unit 310 provides it to the intelligent learning processing unit 320. In addition, information such as a URL for providing an answer to a corresponding query or data may be received from the intelligent learning processing unit 320. Then, the controller 310 accesses the DB 130a of FIG. 1 on the basis of the corresponding URL information, searches for answers or data, and provides them to the learner terminal device 110. Of course, in this process, the control unit 310 may perform various operations with the intelligent learning processing unit 320. Typically, if it is possible to answer a learner's inquiries, the service is provided through a central network method, but if the answer is not possible, the learner and the instructor can communicate through P2P. It can be seen that the control unit 310 performs the same operation as the intelligent learning processing unit 320.

In addition, the control unit 310 stores various information or data processed in the process of performing the intelligent learning service in the storage unit 330, and then, when the intelligent learning processing unit 320 requests it, the corresponding storage unit 330 Can provide information or data. For example, if there is a query, that is, a query from a plurality of learners, it may be stored in the storage unit 330 and then sequentially called and provided to the intelligent learning processing unit 320.

Meanwhile, the controller 310 may include a CPU and a memory as another embodiment of the present invention. Of course, the CPU and memory can be configured as one chip. Accordingly, the CPU can quickly increase the data processing speed by copying the program stored in the intelligent learning processing unit 320 at the beginning of the system operation, loading it into the memory, and executing it. The CPU includes a control circuit, an operation unit (ALU), an instruction interpretation unit, a registry, and the like, and the memory may include RAM. The control circuit is in charge of the control operation, the operation unit performs, for example, an operation operation of binary bit information, and the instruction analysis unit performs an operation of interpreting the machine language of the binary bit so that the control circuit recognizes it. For example, input information is matched to the right side of the lookup table LUT, and machine language that the CPU can recognize is stored on the left side. Therefore, the CPU can recognize the operation to be performed by itself based on the corresponding machine language.

The intelligent learning processing unit 320 may be able to provide academic counseling as well as when a learner has questions about learning in the process of performing the preparation and review, but executes a messenger to perform a conversation with the intelligent conversation robot. It can be seen as implementing a kind of artificial intelligence program. When a learner makes a query through a messenger, the content of the message is analyzed, and based on the analysis result, an appropriate answer with high similarity or data that can be helpful for learning is provided. When conversation content is input through messenger, natural language processing technology is used to analyze it. Analyze plain texts or questions, and understand sentences. Through this, appropriate answers are provided or materials are presented.

Of course, the intelligent learning processing unit 320 can provide answers based on rules prescribed by the system designer at the time of program design, but periodically provides information on answers to be answered or materials to be presented through artificial intelligence programs such as deep learning. Update. In other words, if an answer is provided to a learner's query with 10 data initially, but if the learner finds out that the answer is wrong through repeated questions from the learner, the error is periodically updated and the accuracy is improved. Of course, the materials presented are no exception. For example, if data A is presented based on the result of analysis of the learner's query, but a request for new data is requested from the learner, the existing data A is excluded as data matching the query or given a low weight. Is to do. Through this continuous learning, errors are corrected so that highly accurate responses and data can be provided.

Of course, it is preferable that the intelligent learning processing unit 320 initially executes the program based on the query expected from the instructor and the result of the response in order to provide the learner with a response to the query and data. In other words, it is because, only when there is reference data that can be used, corrections can be made through continuous learning based on this. In this process, for example, when providing data, the intelligent learning processing unit 320 may extract a specific part and provide it to the learner. In other words, since the intelligent learning processing unit 320 can know related contents by analyzing the lecture data provided by the instructor, for example, based on the title of each chapter, a specific part of the query of the learner is extracted and provided. For example, as mentioned in Fig. 2, the part related to the industry size of the block chain is provided to learners by searching for two keywords called block chain and industry size in the part explaining the chart of the lecture data. Is to do.

In addition, the intelligent learning processing unit 320 performs a conversation with the learner through a central network method in a specific situation, that is, in the first situation, in the process of performing a messenger conversation, and the second situation, for example, the robot cannot provide an answer to the learner's query. When it comes to time, the conversation is to take place in a P2P manner through the instructor. In this way, even in the process of performing a conversation in a P2P manner, the intelligent learning processing unit 320 can recognize the conversation content and recognize the context, so that the conversation can be induced. In other words, a university student and a professor may have a strong relationship, but in the case of a general private academy, the relationship between a student and a lecturer may be a little low. In this case, it is because the conversation robot of the intelligent learning processing unit 320 may have to actively mediate the conversation. As described above, the intelligent learning processing unit 320 can be seen to help learners learn by changing and intermediating conversation partners according to the situation.

The storage unit 330 stores various information or data processed under the control of the controller 310. When there is a query of a learner, that is, a query, the query may be sequentially stored in the storage unit 330 and then retrieved in order to be provided to the intelligent learning processing unit 320. In addition, the data obtained from the DB 130a of FIG. 1 may be stored in the storage unit 330 and then provided to the intelligent learning processing unit 320 under the control of the controller 310.

4 is a flowchart illustrating a driving process of the intelligent learning service device of FIG. 1.

For convenience of explanation, referring to FIG. 4 together with FIG. 1, the intelligent learning service device 130 according to an embodiment of the present invention stores lecture data of an instructor, and matches a search word for automatic response search when the lecture data is stored. Save (S400). Of course, here, the search word may be a word (for example, a common noun or a compound noun) or a sentence for each category.

In addition, when there is a learning query based on an interactive messenger from the learner terminal device 110, the intelligent learning service device 130 stores the (pre-)stored lecture data based on the query content of the learning query and the stored search word. It is automatically transmitted to the device 110, and when there is no lecture data to be provided, the learning query is transmitted to the instructor's terminal device 100 (S410). For example, the intelligent learning service device 130 automatically transmits the lecture data previously stored by the instructor to the learner terminal device 110 based on a search word having a similarity with the query content, and the instructor in charge of learning when there is no lecture data to be transmitted. It will be possible to transmit the query content to the teacher's terminal device 100.

In this way, the intelligent learning service device 130 conducts a conversation with a learner in a central network method, and if it is difficult to answer a specific situation, for example, a learner's query, the intelligent learning service device 130 conducts a conversation with the instructor related to the learner's query and makes a query. Answers to or lecture data can be provided.

In addition to the above, the intelligent learning service device 130 performs various operations, but this has been sufficiently described above, and thus the contents will be substituted.

On the other hand, even if all the constituent elements constituting an embodiment of the present invention are described as being combined into one or operating in combination, the present invention is not necessarily limited to this embodiment. That is, within the scope of the object of the present invention, all the constituent elements may be selectively combined and operated in one or more. In addition, although all the components may be implemented as one independent hardware, a program module that performs some or all functions combined in one or more hardware by selectively combining some or all of the components. It may be implemented as a computer program having Codes and code segments constituting the computer program may be easily inferred by those skilled in the art of the present invention. Such a computer program is stored in a non-transitory computer readable media that can be read by a computer and is read and executed by a computer, thereby implementing an embodiment of the present invention.

Here, the non-transitory readable recording medium is not a medium that stores data for a short moment, such as a register, cache, memory, etc., but a medium that stores data semi-permanently and can be read by a device. . Specifically, the above-described programs may be provided by being stored in a non-transitory readable recording medium such as a CD, DVD, hard disk, Blu-ray disk, USB, memory card, ROM, or the like.

In the above, preferred embodiments of the present invention have been illustrated and described, but the present invention is not limited to the specific embodiments described above, and is generally used in the technical field to which the present invention pertains without departing from the gist of the present invention claimed in the claims. Various modifications are possible by those skilled in the art of course, and these modifications should not be individually understood from the technical idea or perspective of the present invention.

100: instructor terminal device 110: learner terminal device
120: communication network 130: intelligent learning service device
300: communication interface unit 310: control unit
320: intelligent learning processing unit 330: storage unit

Claims (6)

A storage unit for storing lecture data of the instructor and matching and storing a search word for automatic response search when the lecture data is stored; And
When there is a learning query based on an interactive messenger from a learner terminal device, the stored lecture data is automatically transmitted to the learner terminal device based on the query content of the learning query and the stored search word, and there is no lecture data to be provided. A control unit that transmits the learning query to the instructor's terminal device of the instructor.
Intelligent learning service device including. The method of claim 1,
The storage unit stores answer contents and lecture data for responding to the query contents as the lecture data,
The controller is an intelligent learning service device that selects and provides one of the stored answer contents and the lecture data based on the query contents. The method of claim 1,
The control unit, while transmitting the learning query to the instructor's terminal device, inquires whether to directly answer the content of the query, and responds to the situation of the learning query according to a result of the response to the inquiry. The method of claim 3,
The control unit, when there is no answer for a specified time after the inquiry, notifies the learner terminal device to answer later. The method of claim 1,
The control unit is an intelligent learning service device that transmits, as the lecture data, extract data obtained by extracting a part related to the content of the query from the lecture data of the instructor. A driving method of an intelligent learning service device comprising a storage unit and a control unit,
Storing lecture data of an instructor, matching a search word for automatic response search when the lecture data is stored, and storing it in the storage unit; And
When there is a learning query based on an interactive messenger from the learner terminal device, the control unit automatically transmits the stored lecture data to the learner terminal device based on the query content of the learning query and the stored search word, and provides Transmitting the learning query to the instructor's terminal device when there is no lecture data;
Driving method of an intelligent learning service device comprising.

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