KR20230151184A - Artificial intelligence natural language processing-based psychological emotion expression and communication improvement system using online work collaboration communication big data - Google Patents

Abstract

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention includes a first user terminal into which communication data of the first user is input; a second user terminal into which communication data of a second user, a collaboration partner of the first user, is input; and a communication data server that analyzes communication data for each user and delivers purified communication data in which communication error elements that may occur between the user and the collaboration partner have been refined.

Description

Online work collaboration communication artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using big data

The present invention relates to an artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online business collaboration communication big data. More specifically, it uses artificial intelligence to reduce emotional misunderstandings during online business collaboration and improve communication. It is about an artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data that can increase efficiency.

Recently, with the global spread of the coronavirus, non-face-to-face (non-face-to-face) work has become a part of daily life, and internet-based non-face-to-face or online work is also expanding in companies.

Additionally, in the IT industry, due to the nature of work, it has become common to conduct work online even before the spread of the coronavirus.

However, when conducting work online, communication may not be smooth, and work results may not be achieved due to this. Because the parties involved in communication do not communicate face-to-face, but communicate through Internet messengers, chatting, etc., or through online meeting tools, they may unintentionally hurt the other party's feelings or express their opinions. Misunderstandings may occur.

In addition, even when dividing work, problems may arise in which work does not progress smoothly by selecting only easy tasks or proceeding with work without considering the work schedules of the collaborators. Since there is a tendency to look only at other people for reasons why work is not progressing smoothly, this can lead to deeper emotional rifts with collaborators.

Therefore, when conducting online collaboration, technology is needed to filter out communication errors and allow collaborators or colleagues to easily understand the content of one's work.

The present applicant proposed the present invention to solve the above problems.

Korean Patent No. 10-2024502 (registration date 2019.09.17.)

The present invention was proposed to solve the above problems. Based on online work, collaboration, and communication big data, expressions are recommended or automatically entered to communicate by best utilizing human emotional elements according to personal work style or communication style. For people who lack the ability to express emotions through language, online work collaboration communication big data improves the ability to express emotions or language through psychological bias and error pattern analysis and recommends or automatically inputs expressions in a way that minimizes misunderstandings. Provides an artificial intelligence (AI) natural language processing-based psychological emotional expression and communication improvement system using .

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention to achieve the above-described tasks is a first user's communication data input. user terminal; a second user terminal into which communication data of a second user, a collaboration partner of the first user, is input; and a communication data server that analyzes communication data for each user and delivers purified communication data in which communication error elements that may occur between the user and the collaboration partner have been refined.

and a data storage unit that receives, stores, and learns user-specific communication data from the first user terminal and the second user terminal, and the user-specific communication data includes conversation history between collaborative communication parties, hierarchical relationships between parties, and parties. conversation patterns or conversation characteristics, characters frequently used by the parties, punctuation marks, emoticons, characters related to emotional expressions, history of use of slang, slang, history of the other party's reactions, presence of disputes between the parties, problems in business progress between the parties Communication data for each user, including history of occurrence, history of misunderstandings between parties, history of mentioning the conversation party to a third party, errors in details of collaborative work, history of misunderstandings, past work processing history, work performance It may include work communication data for each user, including evaluation history, work leader history, work follower history, and work performance attitude.

The communication data server extracts communication patterns and personalities by analyzing communication data for each user accumulated in the data storage unit, extracts work performance trends by analyzing business communication data for each user, and provides standard data for each user. Personal characteristic analysis department that defines; A communication data verification department that determines the presence or absence of errors or biases by applying psychological standards to user-specific communication data or work communication data; And if the communication data verification department determines that the standard data for each user is valid, communication data exchange that corrects the communication data and work communication data to be transmitted between the user and the collaboration partner for accurate communication and work collaboration between the user and the collaboration partner. May include government;

The personal characteristics analysis unit can distinguish whether the content expressed or communicated in the collaboration tool for each user is related to the work result or work content in the collaboration tool, and connect the expression or communication content with the related work result or work content. .

The personal characteristic analysis unit may separate the tasks of each subject responsible for the language used for communication by each user into logical language data and emotional language data.

The communication data correction unit recommends or converts expressions by reflecting the communication patterns or characteristics of each user based on the communication data for each user, or applies psychological theories to the logical language data and emotional language data for each user obtained from the personal characteristic analysis unit. By applying it, it can be determined whether the user lacks logical language expression skills or emotional language expression skills.

The communication data correction unit recommends or inputs expressions that match the work style or communication style for each user derived from the personal characteristic analysis unit and can be communicated while maintaining emotional elements for each user, or psychological biases or errors for each user. Through pattern analysis, expressions that minimize misunderstandings with collaborators can be recommended or entered.

The communication data correction unit analyzes the language of each user and can recommend or input expressions that are advantageous for communication by increasing good feelings between communicating parties and reducing bad feelings or psychological bias.

The communication data verification unit is a cooperation/non-cooperation division that determines whether each user has a tendency to do less work or does more advantageous work than the collaboration partner or team member, a psychological theory application section that determines the presence or absence of psychological bias for each user, or a collaboration unit. It may include at least one of the game theory application units that determine whether each other is betraying work.

It can include a work reminder section that automatically connects, organizes, and reminds collaborating parties of minor work details that are overlooked due to the tendency to remember and recognize work progress by simplifying it.

The task reminder unit may use or provide figures that classify the importance or urgency of the task, or figures that express expressions of emotions or states.

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention allows collaborators or surrounding colleagues to easily understand the content of one's work during online collaboration. .

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention evaluates whether collaborators or colleagues can well understand the content of one's work and determines the index. Because it displays the information, any deficient parts of the work can be automatically supplemented based on this.

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online business collaboration communication big data according to an embodiment of the present invention automatically checks whether work is carried out while complying with work rules related to work progress and personally or emotionally Because it converts words into business-like and rational words, it can prevent misunderstandings in the online communication process and increase the efficiency of collaboration.

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention is an individual's personality by continuously learning big data including communication data or work communication data. You can modify or recommend communication expressions or words to suit your work style.

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online business collaboration communication big data according to an embodiment of the present invention automatically matches the different types of language expressions used by each person to common business communication standards within the company. It can be used for communication by translating other languages so that it can be recorded and communicated.

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention is a system for improving emotional expression and communication in major psychology such as cognitive psychology or social psychology in the case of people who lack the ability to express emotional language. By supplementing or improving language expression skills using researched methods that can minimize various biases and errors, misunderstandings or emotional discord between collaborating parties can be reduced.

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention distinguishes between the expressions of people with selfish tendencies and altruistic tendencies within a team, and these differences are well known. By making it visible, you can reduce misunderstandings about your collaborators.

An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online business collaboration communication big data according to an embodiment of the present invention is a system for improving business intentions when working together on abstract and invisible tasks such as program or software development. Work performance can be improved by automatically recording and analyzing numerous language data during communication and displaying it in an easy and consistent format.

The artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online business collaboration communication big data according to an embodiment of the present invention applies artificial intelligence natural language processing technology to communication big data collected during online business collaboration to convert text. You can tell whether the writer's emotions are positive or negative, and use this to help with collaborative communication.

Figure 1 is a diagram illustrating the concept of an artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention.
Figure 2 is a diagram showing the configuration of an artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention.
Figure 3 is a diagram showing the configuration of the personal characteristics analysis unit of the artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to Figure 2.
Figure 4 is a diagram showing the configuration of the communication data verification unit of the artificial intelligence natural language processing-based psychological emotion expression and communication improvement system using online work collaboration communication big data according to Figure 2.
Figure 5 is a diagram showing the configuration of the communication data correction unit of the artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to Figure 2.

The advantages and/or features of the present invention and methods for achieving them will become clear by referring to the embodiments described in detail below in conjunction with the accompanying drawings. However, the present invention is not limited to the embodiments disclosed below and will be implemented in various different forms, but the present embodiments only serve to ensure that the disclosure of the present invention is complete and are within the scope of common knowledge in the technical field to which the present invention pertains. It is provided to fully inform those who have the scope of the invention, and the present invention is only defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification.

In addition, the preferred embodiments of the present invention to be implemented below are provided in each system function configuration in order to efficiently explain the technical components constituting the present invention, or system functions commonly provided in the technical field to which the present invention pertains. The configuration will be omitted whenever possible, and the description will focus on the functional configuration that must be additionally provided for the present invention. If a person has ordinary knowledge in the technical field to which the present invention pertains, he or she will be able to easily understand the functions of conventionally used components among the functional configurations not shown and omitted below, as well as the omitted configurations as described above. The relationships between elements and components added for the present invention will also be clearly understood.

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

1 is a diagram illustrating the concept of an artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to an embodiment of the present invention, and FIG. 2 is a diagram illustrating an embodiment of the present invention. A diagram showing the configuration of a psychological emotional expression and communication improvement system based on artificial intelligence natural language processing using big data for online work collaboration communication according to Figure 3. Figure 3 shows psychology based on artificial intelligence natural language processing using big data for online work collaboration communication according to Figure 2. Figure 4 shows the configuration of the personal characteristics analysis unit of the emotional expression and communication improvement system. Figure 4 shows the configuration of the communication data verification unit of the artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data according to Figure 2. Figure 5 is a diagram showing the configuration of the communication data correction unit of the artificial intelligence natural language processing-based psychological emotion expression and communication improvement system using online work collaboration communication big data according to Figure 2.

The artificial intelligence natural language processing-based psychological emotional expression and communication improvement system (100, hereinafter referred to as “communication improvement system”) using online work collaboration communication big data according to an embodiment of the present invention shown in Figure 1 is an Internet-based This is a system that can be applied when performing work using a wireless communication network or network, such as web-based or mobile device-based.

The communication improvement system 100 according to an embodiment of the present invention is a communication problem, emotional misunderstanding problem, or work communication problem that may occur in the process of working while a plurality of online-based users collaborate. You can solve the problem or prevent it from occurring.

The communication improvement system 100 according to an embodiment of the present invention stores communication data or work communication data exchanged between a plurality of users (A, B, C) through user terminals 10, 20, and 30, By converting data into data and analyzing big data, communication is carried out by examining emotional factors for each user according to their work style or communication style, preventing unintended misunderstandings or emotional problems from occurring in relationships with the communication partner. This can prevent problems and ultimately increase work performance.

The communication improvement system 100 according to an embodiment of the present invention can improve communication problems that occur during text-based business collaboration.

The communication improvement system 100 according to an embodiment of the present invention solves or improves communication problems that occur during online collaboration by using text data from commercialized collaboration tools such as Jira, Slack, Confluence, Notion, Flow, KakaoTalk, etc. can do.

Here, the user terminals 10, 20, and 30 may include terminals capable of sending and receiving data wired or wirelessly, such as desktop computers, laptop computers, and smartphones.

The communication improvement system 100 according to an embodiment of the present invention includes a communication data server 200 that receives, stores, and analyzes communication data including communication data and work communication data from user terminals 10, 20, and 30. may include. In the communication improvement system 100 according to an embodiment of the present invention, communication data or communication big data may include data expressed in text form.

Referring to Figures 1 and 2, the communication improvement system 100 according to an embodiment of the present invention includes a first user terminal 10 into which communication data of a first user (A) is input; a second user terminal (20) into which communication data of a second user (B), a collaboration partner of the first user (A), is input; and a communication data server 200 that analyzes communication data for each user and delivers purified communication data in which communication error elements that may occur between the user and the collaboration partner have been refined.

Here, “refined communication data” is communication data that has previously eliminated any unintended emotional discord or misunderstanding that may occur between communicating or collaborating parties, and is a concept that includes communication data and work communication data.

Additionally, communication data is a concept that includes communication data and business communication data, and the communication data server 200 is a server that handles not only communication data but also business communication data.

Figure 2 illustrates two communicating or collaborating parties. The two parties are only an example, and the communication improvement system 100 according to an embodiment of the present invention can be applied even when two or more parties are involved.

The communication improvement system 100 according to an embodiment of the present invention transmits communication data and work communication data for each user from the communication data server 200, the first user terminal 10, and the second user terminal 20. It may include a data storage unit 300 that receives, stores, and learns.

Here, the data storage unit 300 can store communication data and business communication data as big data, and applies artificial intelligence (AI) or machine learning to big data to learn the stored big data to create a learning model. can be derived.

Here, the communication data includes data (sentences) exchanged with the communicating party, words exchanged during a video conference, facial expressions or actions observed during a video conference, and writing (text) written on an in-house bulletin board or work bulletin board, etc. The work communication data is data that includes emails, messages, work records, work lists, etc. sent and received related to work that must be performed collaboratively, and may mostly include text-based data.

For example, user-specific communication data includes the conversation history between collaborative communication parties, the hierarchical relationship between the parties, the conversation patterns or conversation characteristics of the parties, characters, punctuation marks, emoticons, characters related to emotional expressions, and slang frequently used by the parties. , including data on the history of using profanity, the history of the other party's reaction, the presence or absence of quarrels between the parties, the history of problems occurring in the process of work between the parties, the history of misunderstandings between the parties, and the history of mentioning the conversation party to a third party. In addition, the work communication data for each user may include data on errors in details of collaborative work, misunderstanding history, past work processing history, work performance evaluation history, work leader history, work follower history, and work performance attitude. there is.

The user's face can be photographed during a video conference using the cameras 16 and 26 provided in the user terminals 10 and 20, and the user can send a messenger message or talk to the video conference participants through the user terminals 10 and 20. The facial expression when doing can be filmed with a camera (16, 26).

The moment the user inputs a message into the user terminal 10, 20, the change in the user's facial expression at the moment of speaking in a video conference is acquired with a camera 16, 126, and the image data (video data) obtained from these cameras 16, 26 Including) can be transmitted to the communication data server 200.

The communication data server 200 analyzes communication data and work communication data including messages or words entered by the user to more accurately determine personal style by considering changes in facial expressions for each user when defining a personal work style or communication style. It can be defined. Since human emotions are generally expressed in facial expressions, the communication data server 200 analyzes the user's emotions or emotional changes in consideration of facial expression changes and determines whether these emotional changes may cause misunderstanding in communication or business communication. You can determine whether it exists.

Referring to FIG. 2, the communication data server 200 of the communication improvement system 100 according to an embodiment of the present invention includes a task reminder unit 210, a communication data correction unit 230, and a communication data verification unit 250. ) and a personal characteristic analysis unit 270.

The communication improvement system 100 according to an embodiment of the present invention requires a counterparty for communication and collaboration. Referring to FIG. 2, communication data (communication data and work communication data) input by the first user (A) through the first user terminal 10 is transmitted to the second user (B) through the second user terminal 20. ), and the communication data input by the second user (B) through the second user terminal (20) is assumed to be transmitted to the first user (A) through the first user terminal (10). Additionally, in some cases, it may be assumed that communication data is delivered to multiple parties who need to communicate in relation to work, rather than to a specific communication partner.

The communication data server 200 analyzes communication data for each user accumulated in the data storage unit 300 to extract communication patterns and personalities, and extracts work performance trends by analyzing business communication data for each user. a personal characteristic analysis unit 270 that defines standard data for each user; A communication data verification unit 250 that determines the presence or absence of errors or biases by applying psychological standards to user-specific communication data or work communication data; And when the communication data verification unit 250 determines that the standard data for each user is valid, it corrects the communication data and work communication data to be transmitted between the user and the collaboration partner for accurate communication and work collaboration between the user and the collaboration partner. It may include a communication data correction unit 230.

Referring to FIG. 2, it is shown that communication data input through the first and second user terminals 10 and 20 are directly transmitted to the data storage unit 300, and the communication data of the communication data server 200 It may be transmitted to the data storage unit 300 after passing through the correction unit 230, the communication data verification unit 250, and the personal characteristic analysis unit 270.

First, communication data and work communication data input through the first user terminal 10 or the second user terminal 20 may be stored in the data storage unit 300. At this time, the data storage unit 300 can convert user-specific communication data into text-based big data by accumulating communication data and work communication data for each user.

In addition, data (reference data) on the communication style and work style of each user obtained by analyzing the communication data and work communication data for each user in the communication data server 200 may also be stored in the data storage unit 300. . The reference data stored in the data storage unit 300 is transmitted to the communication data server 200 and used to purify the user's communication data, recommend communication data that can prevent errors or misunderstandings, or automatically enter expressions. You can.

User-specific communication data (communication data and work communication data) stored in the data storage unit 300 is transmitted to the personal characteristic analysis unit 270 of the communication data server 200 to determine the user's (individual) communication style or work style. Can be used to define .

As shown in Figure 3, the personal characteristics analysis unit 270 includes a communication data history analysis unit 271, a communication data characteristic analysis unit 272, a communication data emotion analysis unit 273, and a communication data facial expression analysis unit ( 274), a language analysis unit 275, a work style analysis unit 276, and a communication language analysis unit 277.

Here, the communication data history analysis unit 271 determines the contents of past communication between parties involved in communication or work communication or between colleagues who need collaboration to proceed with work, the content of work communication, and the time of communication or work communication. It is possible to analyze whether misunderstandings or emotional discord have occurred between each other.

The communication data history analysis unit 271 can analyze and find the cause of misunderstanding or emotional discord by considering not only texts, sentences, and words exchanged between communication or business communication parties, but also various surrounding environmental factors. For example, the conversation history between the parties involved in business communication that requires communication or collaboration, the relationship between the parties (superior/subordinate relationship, position, etc.), the conversation patterns and conversation characteristics (habits) of the parties, characters and punctuation frequently used by the parties, etc. , emoticons, characters or symbols expressing emotions, history of using slang or slang, history of reactions to the other party, presence or absence of quarrels between parties, history of problems occurring during work, history of mentioning the conversation party to a third party. Data such as can be analyzed.

The communication data characteristic analysis unit 272 can find individual characteristics (patterns or styles) by analyzing the individual history analyzed in the communication data history analysis unit 271, and can identify the cause of errors or emotional discord during communication from these individual characteristics. You can find it.

In order to more accurately analyze the causes of communication errors or emotional discord, the communication improvement system 100 according to the present invention not only analyzes the writings or words exchanged between users, but also what emotions are expressed when writing or speaking, and what writings the other party writes. It may include a communication data emotion analysis unit 273 that analyzes whether there has been a change in the user's emotion in words or words.

Unlike when meeting or working face to face, when people are spatially separated from each other and hold meetings online, they cannot see the expressions on each other's faces. If you can see the other person's face, you can guess the other person's emotions through changes in expression on the other person's face, and you can determine for yourself which of your words and actions had a negative impact on the other person's emotions and pay attention to them, which worsens emotional discord. You can prevent it from happening. However, online, in a situation where the parties cannot see each other's faces, they have to understand the other person's emotions only through the texts, sentences, and messages exchanged between them, which is not easy. Therefore, misunderstandings or emotional discord may occur due to the inability to properly understand the other person's emotions contained in the other person's message.

The communication data emotion analysis unit 273 analyzes the message content and the other party's messages for each user, or analyzes the presence or absence of expressions, words, symbols, emoticons, etc. that are repeatedly used in relation to emotional expressions, and determines whether the user has any specific information. When using expressions or words, you can find out whether they can be seen as expressing emotions.

However, it is not easy to accurately find the user's emotions only with specific content or characteristics included in the message. To solve this difficulty, the communication improvement system 100 according to an embodiment of the present invention includes a communication data facial expression analysis unit 274. may include.

In the case of the present invention, the user's face can be captured in real time while the user inputs a message into the terminal using the cameras 16 and 26 provided in the user terminal 10 and 20, and the communication data expression analysis unit 274 It is possible to find the characteristics of emotional changes for each user by receiving face shooting data, time data, etc. from the cameras 16 and 26 and directly analyzing the change in the user's facial expression.

When the user sends a messenger message or speaks to a video conference participant through the user terminal (10, 20), the facial expression may be captured by the camera (16, 26), and the user's facial expression may be captured by the camera (16, 26). At the moment of entering a message, the user's facial expression change at the moment of speaking in a video conference is acquired by a camera (16, 126), and the image data (including video data) obtained from these cameras (16, 26) is sent to the communication data server (200). The communication data can be transmitted to the facial expression analysis unit 274.

The language analysis unit 275 determines the type of language used by each user and provides translation, thereby preventing misunderstandings or emotional discord between parties using different languages during communication or work. .

The language analysis unit 275 can read the content of the message input by each user to determine what language the message is based on and whether the languages used by the communicating parties are the same or different. If you speak different languages, you can translate into the other person's language to enable communication. At this time, it is necessary to take into account the characteristics of the language and translate to avoid misunderstandings.

The work style analysis unit 276 can analyze each user's attitude toward work requiring collaboration and work performance style. For example, in a collaborative relationship where user A completes a specific task first and then passes it on to user B, user B can then proceed with the task, user A has a style of working as the deadline approaches and works in advance before the deadline arrives. Work can be done in one of the following styles: a style that completes tasks, or a style that progresses work little by little considering the entire period. However, if User B does not know User A's work style, misunderstandings may occur during collaboration.

In addition, the work style analysis unit 276 of the personal characteristic analysis unit 270 can check whether or not each user complies with work rules, or checks the tendency to do less work than the other person or team member, or to do only advantageous work. For example, if user A performs work by complying well with the work rules, while user B does not follow the work rules well, the work style analysis unit 276 analyzes compliance with the work rules for each user and determines individual characteristics. It can be defined as: In addition, if user A does not avoid difficult tasks among collaborative tasks, but user B tends to only do easy tasks, the work style analysis unit 276 analyzes the styles of each user and adjusts them to prevent discord between the collaboration parties. It can be used to

In this way, the work style analysis unit 276 can prevent misunderstandings from occurring during work communication by analyzing each user's work handling or processing style and using this in the relationship with the collaboration partner.

The communication language analysis unit 277 can separate the tasks of each subject responsible for the language used for communication for each user into logical language data and emotional language data. Here, logical language data refers to language data used for work-related communication, and emotional language data refers to language data used to express emotions.

The communication language analysis unit 277 can help determine whether an individual user lacks logical language expression or emotional language expression by dividing the communication language for each user into logical language data and emotional language data.

The communication language analysis unit 277 can determine whether the emotions of the person writing the text are positive or negative by collecting the communication big data stored in the data storage unit 300 and applying artificial intelligence natural language processing technology to the communication big data. , these results can be used to help with collaborative communication for each user.

The communication language analysis unit 277 uses natural language processing technology such as BERT (Bidirectional Encoder Representations from Transformers) or GPT-3 (Generation Pre-trained Transformer 3), which are natural language processing technologies provided by Google or Microsoft (MS), or deep learning. By using an artificial intelligence (AI) library that implements various technologies, it is possible to understand the emotions of each user.

Meanwhile, the personal characteristic analysis unit 270 can determine whether a user or individual does relatively more or less work related to collaboration, or determines whether communication expressions are lacking. At this time, the personal characteristic analysis unit 270 connects the content that the user or individual expresses or communicates in collaboration tools such as Slack, Jira, Confluence, Notion, Flow, and KakaoTalk with any work results or work content in the collaboration tool. It can also be equipped with a function to distinguish whether it is related or related, and to connect numerous work contents and corresponding work communication contents. For example, if a user or individual analyzes a collaboration-related task as having the characteristic of working relatively little, it is necessary to determine which task the user or individual works a little on. Since this user may work less on task A but work a lot on task B, it is necessary to be able to connect the individual's characteristics with related task content or work results to determine the exact characteristics of the individual. For this purpose, the personal characteristic analysis unit 270 determines whether the content expressed or communicated by the user or individual in collaboration tools such as Slack, Jira, Confluence, Notion, Flow, and KakaoTalk is related to any work results within the collaboration tool. By analyzing whether there are any, it is possible to connect work results or work content related to personal characteristics, including expression or communication content. At this time, the personal characteristic analysis unit 270 may automatically connect personal characteristics and the corresponding work results or work contents using an artificial intelligence (AI) data connection function.

Communication data whose characteristics for each user have been analyzed in the personal characteristic analysis unit 270 may be transmitted to the communication data verification unit 250.

Referring to FIG. 4, the communication data verification unit 250 includes a cooperation/non-cooperation classification unit 251 that determines whether each user has a tendency to do less work or perform more advantageous work than his/her collaboration partner or team member, and a psychological/non-cooperation classification unit 251 for each user. It may include at least one of a psychological theory application unit 252 that determines the presence or absence of bias or a game theory application unit 253 that determines whether each other betrays work during collaboration.

The cooperation/non-cooperation classification unit 251 may operate in conjunction with the work style analysis unit 276. Based on the work style of each user analyzed in the work style analysis unit 276, if user A is judged to be cooperative in a task requiring collaboration and user B is judged to be non-cooperative, user B is excluded from the task or cooperative. attitude can be induced.

The cooperation/non-cooperation classification unit 251 may analyze the reasons why non-cooperative users are uncooperative in collaborative work. By finding and correcting the causes of uncooperative attitudes, it is possible to guide collaborating parties to have a cooperative attitude toward work.

The psychological theory application unit 252 can analyze from a psychological perspective the causes of misunderstandings or emotional discord during communication or work communication. For example, when User A and User B collaborate and work does not proceed well or results are not achieved, User A may blame User B. The reason User A blames User B is because people generally tend to think that there is no problem themselves, but that someone else has a problem. This tendency is due to cognitive bias defined in cognitive psychology or social psychology. The psychological theory application unit 252 may apply the theory of cognitive bias defined in psychology to prevent cognitive bias for each user from occurring.

The psychological theory application unit 252 can automatically correct or minimize various biases and misunderstandings for each user according to various verified psychological theories and deliver them to the other party.

The game theory application unit 253 may be included in the psychological theory application unit 252. The game theory application unit 253 can apply "game theory (prisoner's dilemma, etc.)" to work collaboration and automatically adjust the parties to communicate based on trust without betraying each other during work. For example, the game theory application unit 253 automatically distinguishes between "cooperation" and "betrayal" when collaborating together, similar to the Tit for tat (TFT) strategy, and reminds the entire team of optimal collaboration performance. can be derived. Here, "betrayal" can be defined as an attitude of trying to do less than the other person or only do more advantageous things while carrying out detailed work, contrary to appearance, and this can be easily seen and reminded to each person with a tit-for-tat strategy. there is.

In addition, the psychological theory application unit 252 or the game theory application unit 253 applies psychological theories to the user-specific logical language data and emotional language data obtained from the communication language analysis unit 277, thereby improving the user's logical language expression ability. You can determine whether your ability to express emotions verbally is lacking.

The communication data verified by the communication data verification unit 250 may be passed through the communication data correction unit 230 and then finally delivered to the communication party or the communication counterpart.

The communication data correction unit 230 may recommend or convert expressions by reflecting communication patterns or characteristics of each user based on user-specific communication data (communication data and work communication data).

Referring to FIG. 5, the communication data recommendation unit 230 includes a message purification unit 231, a message recommendation unit 232, a language conversion unit 233, a work situation reflection unit 234, and a counterpart consideration unit 235. It may include at least one of:

The message purification unit 231 considers each user's communication style or work style obtained from the personal characteristic analysis unit 270, or the user's psychological bias obtained from the communication data verification unit 250, to prevent the user's message from being misunderstood by the other party. You can create a purified message so as not to trigger it and send this message to the other person.

The message recommendation unit 232 may be formed integrally with the message purification unit 231 or may be provided separately. The message recommendation unit 232 may work in conjunction with the message purification unit 231 to recommend messages or expressions that enable intended communication or business communication between parties without causing misunderstanding or emotional discord in the other party. At this time, considering the verification results of the communication data verification unit 250 and the characteristics of each user found in the personal characteristics analysis unit 270, a message that does not cause misunderstanding by the other party while maintaining the intention of the user entering the message can be recommended. You can.

It is desirable for the message recommendation unit 232 to recommend work-priority messages so that work can proceed smoothly between collaborating parties.

Meanwhile, the message purification unit 231 or the message recommendation unit 232 uses the logical language data and emotional language data for each user obtained from the communication language analysis unit 277 to the psychological theory application unit 252 or the game theory application unit 253. ), that is, whether the user lacks logical language expression skills or emotional language expression skills, a message that can improve the shortcomings can be recommended. For example, for users who lack emotional verbal expression skills, words that can improve emotional verbal expression skills are recommended, and for users who lack business-related logical verbal expression skills, logical expressions can be supplemented. You can recommend messages that are available.

The language conversion unit 233 is linked with the language analysis unit 275, and when the languages between the communicating parties are different, the language conversion unit 233 can transmit a message, etc. by translating it into the other party's language. The language conversion unit 233 is required to translate the message so that the recipient of the message can receive it without misunderstanding while not damaging the intention of the person giving the message, taking into account the unique characteristics of the language and the characteristics of each user.

The work situation reflection unit 234 can recommend a message that should be delivered to the other party depending on the progress of the work between the collaborating parties. For example, if the user giving the message must complete the task first, if the task is progressing near the deadline, or if the task is completed before the deadline, the message entered by the message user may be corrected or recommended. I can give it.

The other party's consideration unit 235 can recommend or automatically enter expressions that can eliminate mutual misunderstanding by considering the characteristics of not only the party giving the message but also the characteristics of the collaborating party receiving the message.

In this way, the communication data correction unit 230 corrects the message entered by a user before it reaches the other party and delivers refined communication data free of elements that may cause misunderstanding to the other party. In this process, the characteristics or circumstances of both communicating parties are corrected. Taking all of these factors into consideration, we recommend expressions that do not cause misunderstandings or emotional discord between parties. At this time, you should be able to recommend expressions that will ensure smooth work processing while preventing misunderstandings or emotional discord.

In this way, the communication data correction unit 230 recommends or inputs an expression that matches the work style or communication style of each user derived from the personal characteristic analysis unit 270 and can be communicated while maintaining the emotional elements of each user. , The communication data verification unit 250 can recommend or input expressions that minimize misunderstandings with collaboration partners through analysis of psychological biases or error patterns for each user.

In addition, the communication data correction unit 230 can analyze the language of each user and recommend or input expressions that are advantageous for communication by increasing good feelings between communicating parties and reducing bad feelings or psychological bias. In other words, if each user uses a different language, the communication data correction unit 230 translates it into the other party's language and presents the communication data or work communication data to the collaboration partner, while increasing good feelings between the communicating parties and reducing bad feelings or It can be translated to reduce psychological bias.

Meanwhile, the communication data server 200 of the communication improvement system 100 according to an embodiment of the present invention automatically connects minor work details that are overlooked due to the tendency to remember and recognize work progress between collaborating parties. It may include a task reminder unit 210 that gives, organizes, and reminds people.

Those who carry out intangible tasks tend to remember and recognize tasks by simplifying them to their advantage or convenience (cognitive psychology). The task reminder unit 210 takes into account these cognitive tendencies and Work details can also be automatically connected, organized, and reminded.

Collaborating parties tend to group, simplify, and store complex and similar matters, and this tendency can lead to errors, misunderstandings, and differences regarding specific detailed tasks in reality. The task reminder unit 210 can automatically express detailed and specific task-related data as accurate and visual analysis data, allowing everyone to accurately share the same task progress status.

Since each person has different emotions and the degree to which they think about each task, the degree to which they accept them is also different. Therefore, the task reminder unit 210 automatically quantifies or records the importance or status of tasks as numerical data and continuously By correcting this, the collaborating parties can share the other party's status, etc.

The task reminder unit 210 classifies the importance of each task, the urgency of each task, and the work stress of each task for each individual, and visualizes and shares them with numerical data to ensure accurate work-related communication between collaborating parties. And it can help you understand the other person’s situation. For example, when communicating for work collaboration, use a number that classifies the importance or urgency of work from 1 to 10, or a number that represents the expression or state of emotion (for example, the emotional state of being angry is rated from 1 to 10). By using or providing (numbers expressed separately), it can help collaborating parties understand the emotional state of the other party to accurately communicate work-related issues.

The online business communication system according to an embodiment of the present invention described above is basically an artificial intelligence (AI) system based on business communication big data, and communicates by making the best use of human emotional elements according to personal work style or communication style. It is a system that recommends or automatically enters expressions as much as possible and minimizes misunderstandings through psychological bias and error pattern analysis.

In other words, it can be viewed as a type of artificial intelligence-based natural language processing technology that improves business communication by analyzing human language to increase good emotions and reduce bad emotions and psychological biases, and can be used to utilize this to create metaverse-based online (virtual reality) ) It can also be applied to business communication systems.

The system described above may be implemented with hardware components, software components, and/or a combination of hardware components and software components. For example, the systems and components described in the embodiments may include, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable array (FPA), It may be implemented using one or more general-purpose or special-purpose computers, such as a programmable logic unit (PLU), microprocessor, or any other device capable of executing and responding to instructions. A system may run an operating system (OS) and one or more software applications running on the operating system. Additionally, the system may access, store, manipulate, process, and generate data in response to the execution of software. For convenience of understanding, there are cases where the components of the system are described as being used one by one, but those skilled in the art will understand that the system or components include a plurality of processing elements and/or It can be seen that it may include multiple types of processing elements. For example, a system may include multiple processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are possible.

Software may include a computer program, code, instructions, or a combination of one or more of these, and may configure a system or processing unit, independently or collectively, to operate as desired. can be commanded. Software and/or data may be used by any type of machine, component, physical device, virtual equipment, computer storage medium or device to be interpreted by or to provide instructions or data to the system. It can be permanently or temporarily embodied in a transmitted signal wave. Software may be distributed over networked computer systems and stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

As described above, the embodiments of the present invention have been described with specific details such as specific components and limited examples and drawings, but this is only provided to facilitate a more general understanding of the present invention, and the present invention is limited to the above embodiments. This does not mean that various modifications and variations can be made from this description by those skilled in the art. Accordingly, the spirit of the present invention should not be limited to the described embodiments, and all claims that are equivalent or equivalent to the claims as well as the following claims fall within the scope of the present invention.

100: Online work collaboration communication artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using big data
200: communication data server
210: Work reminder department
230: Communication Data Correction Department
250: Communication data verification department
270: Personal characteristics analysis unit
300: data storage unit

Claims (11)

a first user terminal into which communication data of the first user is input;
a second user terminal into which communication data of a second user, a collaboration partner of the first user, is input; and
A communication data server that analyzes communication data for each user and delivers purified communication data in which communication error elements that may occur between the user and the collaboration partner have been refined;
An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data.
According to paragraph 1,
A data storage unit that receives communication data for each user from the first user terminal and the second user terminal, stores it, and learns it,
The communication data for each user includes the conversation history between the collaborative communication parties, the hierarchical relationship between the parties, the conversation patterns or conversation characteristics of the parties, the characters frequently used by the parties, punctuation marks, emoticons, characters related to emotional expressions, slang, and slang. Communication data for each user, including history, history of the other party's reaction, presence or absence of quarrels between the parties, history of problems occurring in the process of work between the parties, history of misunderstandings between the parties, history of mentioning the conversation party to a third party, and , Online work collaboration, which includes work communication data for each user, including errors in details of collaborative work, misunderstanding history, past work processing history, work performance evaluation history, work leader history, work follower history, and work performance attitude. An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using communication big data.
According to paragraph 2,
The communication data server,
a personal characteristic analysis unit that analyzes communication data for each user accumulated in the data storage unit to extract communication patterns and personalities, analyzes work communication data for each user to extract work performance trends, and defines standard data for each user;
A communication data verification department that determines the presence or absence of errors or biases by applying psychological standards to user-specific communication data or work communication data; and
If the communication data verification unit determines that the standard data for each user is valid, the communication data correction unit corrects the communication data and work communication data to be transmitted between the user and the collaboration partner for accurate communication and business collaboration between the user and the collaboration partner. An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data, including;
According to paragraph 3,
The personal characteristic analysis unit distinguishes whether the content expressed or communicated in the collaboration tool for each user is related to the work result or work content in the collaboration tool, and connects the expression or communication content with the related work result or work content. Online work collaboration communication Big data-based artificial intelligence natural language processing-based psychological emotional expression and communication improvement system.
According to paragraph 3,
The personal characteristic analysis unit separates the language used for communication by each user into logical language data and emotional language data for each topic, and psychological and emotional expression based on artificial intelligence natural language processing using online work collaboration communication big data. and communication improvement system.
According to clause 5,
The communication data correction unit recommends or converts expressions by reflecting user-specific communication patterns or characteristics based on user-specific communication data, or psychological theory based on user-specific logical language data and emotional language data obtained from the personal characteristic analysis unit. An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data that determines whether the user lacks logical or emotional language expression skills by applying .
According to paragraph 4,
The communication data correction unit recommends or inputs expressions that match the work style or communication style for each user derived from the personal characteristic analysis unit and can be communicated while maintaining emotional elements for each user, or psychological biases or errors for each user. An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online work collaboration communication big data that recommends or inputs expressions that minimize misunderstandings with collaborators through pattern analysis.
According to paragraph 4,
The communication data correction department analyzes the language of each user and recommends or inputs expressions that are advantageous for communication by increasing good feelings between communicating parties and reducing bad feelings or psychological bias. Artificial intelligence natural language using big data for online work collaboration communication A processing-based psychological emotional expression and communication improvement system.
According to any one of claims 4 to 8,
The communication data verification unit,
A cooperation/non-cooperation division that determines whether each user has a tendency to do less work or do more advantageous work than the collaboration partner or team member, a psychological theory application section that determines the presence or absence of psychological bias for each user, or whether work is betrayed by each other during collaboration. An artificial intelligence natural language processing-based psychological emotional expression and communication improvement system using online business collaboration communication big data that includes at least one of the game theory application parts to determine whether or not
According to clause 9,
Artificial intelligence natural language processing-based psychology using online work collaboration communication big data, including a work reminder section that automatically connects, organizes, and reminds collaborating parties of minor work details that are overlooked due to the tendency to simplify and remember and recognize work progress A system for improving emotional expression and communication.
According to clause 10,
The work reminder department uses or provides numbers that classify the importance or urgency of work, expressions of emotions, or numbers that indicate the state, improving psychological emotional expression and communication based on artificial intelligence natural language processing using online work collaboration communication big data. system.