Artificial intelligence-based method and system for automatically matching content creator and company

Abstract

The present invention relates to a method and system for automatically matching a content creator and a company on the basis of artificial intelligence, and, more specifically, to a method and system for automatically matching a content creator and a company on the basis of artificial intelligence by identifying the needs of the company.

Description

AI-based automatic matching method and system between content creators and companies

[0001] The present invention relates to a method and system for automatically matching content creators and companies based on artificial intelligence, and more specifically, to a method and system for automatically matching content creators and companies based on artificial intelligence by identifying the needs of companies.

[0002] Existing recruitment platforms are currently structured entirely around text-based content, including job postings, resumes, and portfolios, in order to provide standardized recruitment services across various industries. This presents a problem in that such existing platforms are unsuitable for recruiting creators who produce content in diverse formats, such as video, music, design, and photography.

[0003] Furthermore, from the perspective of companies or project organizers, there was a problem in that hiring creators was difficult because they were traditionally recommended through personal connections, making it hard to recruit creators with content creation styles or personalities suitable for the specific work or company characteristics they intended to produce.

[0004] Furthermore, from the creators' perspective, there was a problem in that, due to the limitations of existing recruitment platforms, it was difficult to find opportunities to apply for companies or production projects suitable for their content creation style or personality, or to interact with other creators with similar styles and personalities and seek advice.

[0005] Therefore, there is a need for a method to equip a content portfolio that aligns with the company's preferred characteristics regarding the content to be produced, and to automatically match creators with personality traits suitable for the company's internal environment to the company.

[0006] The present invention was devised to solve the aforementioned conventional problems, and its purpose is to automatically match a creator with personality traits suitable for the company's internal environment with the company, while possessing a content portfolio that matches the company's preference characteristics for the content to be produced.

[0007] The present invention aims to match a creator suitable for both the company's preferred creation style and internal environment by analyzing not only the company's preferred characteristics regarding content but also the company's internal environment factors, thereby enabling matching that considers both the company's preferred characteristics regarding content creation and the internal environment characteristics.

[0008] The purpose of the present invention is to enable more accurate matching between creators and companies by continuously performing the extraction of company elements that can serve as new considerations from survey responses and feedback information, and the extraction of company elements that may be deemed unsuitable as considerations for matching, thereby customizing the list of company elements.

[0009] The objectives of the present invention are not limited to those mentioned above, and other unmentioned objectives will be clearly understood from the description below.

[0010] According to embodiments of the present invention, an artificial intelligence-based automatic matching method between a content creator and a company, performed by an electronic device, comprises: a step of obtaining company profile information and recruitment information from a first user terminal of a company representative; a step of collecting posts and news content regarding said company from a plurality of homepages, communities, and portal sites; a step of obtaining information on the company's preferred characteristics and preferred creative style regarding content from the recruitment information, posts, and news content regarding said company using a first artificial intelligence model; a step of providing a plurality of surveys for analyzing the internal environment of said company to the first user terminal using a second artificial intelligence model, and receiving survey responses for each of the plurality of surveys from the first user terminal; a step of generating company characteristics for each of a plurality of company elements representing the internal environment of said company based on the result of analyzing the received survey responses using the second artificial intelligence model; a step of generating information on the internal environment of said company based on the company characteristics for each of the plurality of company elements; and a step of associating the information on the company's preferred characteristics regarding content, the information on the preferred creative style, and the information on the internal environment of said company with the profile information and storing them in a database of said electronic device. The method may include: a step of determining a content creator matched with the company as recommendation information based on the above-mentioned preferred feature information, the above-mentioned preferred creative style information, and the above-mentioned internal environment information; a step of providing the determined recommendation information to the first user terminal; and a step of updating a list of company elements including the plurality of company elements based on the results of analyzing the survey response and feedback information regarding the recommendation information.

[0011] According to embodiments of the present invention, the preference feature information of the company can be obtained by analyzing features extracted from content identified in the company's recruitment information, posts and news content regarding the company.

[0012] According to embodiments of the present invention, the preferred creative style information can be obtained based on calculating the similarity of preferred feature information for one or more contents.

[0013] According to embodiments of the present invention, a survey response for each of the plurality of surveys received from the first user terminal is composed of text information in the form of a sentence, and based on analyzing the text information in the form of a sentence, it can be identified which of the plurality of corporate elements each survey response includes content regarding.

[0014] According to embodiments of the present invention, an artificial intelligence-based automatic matching method between content creators and companies may further include: a step of identifying that the survey response contains content regarding a company element different from the plurality of company elements based on analyzing the sentence-form text information; and a step of obtaining a company element output as a result of the clustering by performing artificial intelligence-based clustering based on the identification of the content regarding the different company element.

[0015] According to embodiments of the present invention, an artificial intelligence-based automatic matching method between a content creator and a company may further include: receiving feedback information regarding recommendation information from the first user terminal; identifying a company element among the plurality of company elements that exhibits a similarity level below a predetermined standard with respect to the recommendation information based on the feedback information; and determining the identified company element as a company element to be discarded when the plurality of feedback information is received that exhibits a similarity level below the predetermined standard with respect to the identified company element.

[0016] According to embodiments of the present invention, the step of updating the list of corporate elements may include the step of updating the list of corporate elements based on at least one of adding a corporate element output as a result of the clustering to the list of corporate elements or discarding a corporate element to be discarded from the list of corporate elements.

[0017] According to embodiments of the present invention, the step of determining a content creator matched with the company as recommendation information may include: determining a plurality of content creators having content feature information and creation style information corresponding to the preference feature information and the preference creation style information; and determining one or more content creators having personality information corresponding to the internal environment information among the plurality of content creators.

[0018] The present invention was devised to solve the aforementioned conventional problems, and enables a creator with personality traits suitable for the company's internal environment to be automatically matched to the company while possessing a content portfolio that matches the company's preference characteristics for the content to be produced.

[0019] The present invention enables matching that considers both the company's preferred characteristics regarding content creation and internal environmental characteristics by analyzing not only the company's preferred characteristics regarding content but also the company's internal environmental factors, thereby making it possible to match a creator suitable for both the company's preferred creation style and internal environment.

[0020] The present invention enables more accurate matching in the matching between creators and companies by continuously performing the extraction of company elements that can serve as new considerations from survey responses and feedback information, and the extraction of company elements that may be deemed unsuitable as considerations for matching, thereby customizing the list of company elements.

[0021] FIG. 1 is an example diagram of the configuration of a system according to embodiments.

[0022] FIG. 2 is a flowchart regarding a method for performing automatic matching between AI-based content creators and companies according to embodiments.

[0023] FIG. 3 is an example diagram regarding the update of a list of corporate elements according to embodiments.

[0024] FIG. 4 is a configuration diagram of an electronic device according to embodiments of the present invention.

[0025] Hereinafter, embodiments are described in detail with reference to the attached drawings. However, various modifications may be made to the embodiments, and thus the scope of the patent application is not limited or restricted by these embodiments. It should be understood that all modifications, equivalents, and substitutions to the embodiments are included within the scope of the rights.

[0026] Specific structural or functional descriptions of the embodiments are disclosed for illustrative purposes only and may be modified and implemented in various forms. Accordingly, the embodiments are not limited to the specific disclosed forms, and the scope of this specification includes modifications, equivalents, or substitutions that fall within the technical concept.

[0027] Terms such as "first" or "second" may be used to describe various components, but these terms should be interpreted solely for the purpose of distinguishing one component from another. For example, the first component may be named the second component, and similarly, the second component may be named the first component.

[0028] When it is stated that a component is "connected" to another component, it should be understood that it may be directly connected to or joined to that other component, or that there may be other components in between.

[0029] The terms used in the embodiments are for illustrative purposes only and should not be interpreted as intended to be limiting. Singular expressions include plural expressions unless the context clearly indicates otherwise. In this specification, terms such as "comprising" or "having" are intended to indicate the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0030] Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by those skilled in the art to which the embodiments pertain. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an ideal or overly formal sense unless explicitly defined in this application.

[0031] In addition, when describing with reference to the attached drawings, identical components are assigned the same reference numeral regardless of drawing symbols, and redundant descriptions thereof are omitted. In describing the embodiments, if it is determined that a detailed description of related prior art could unnecessarily obscure the essence of the embodiments, such detailed description is omitted.

[0032] The embodiments can be implemented in various forms of products such as personal computers, laptop computers, tablet computers, smartphones, televisions, smart home appliances, intelligent automobiles, kiosks, and wearable devices.

[0033] FIG. 1 is an exemplary configuration diagram of a system (100) according to embodiments of the present invention. The system (100) may be a system that operates an AI-based matching service between creators and companies based on multilateral automatic matching based on individual creators' portfolios.

[0034] Referring to FIG. 1, the system (100) may include an electronic device (110), creator terminals (120-1 to 120-m) and corporate representative terminals (130-1 to 130-n). The electronic device (110), creator terminals (120-1 to 120-m) and corporate representative terminals (130-1 to 130-n) may be connected via wired or wireless communication through a network (140).

[0035] According to embodiments, the electronic device (110) may be a server device that operates the platform of the service described above. The service may be operated through an application or through a website. In order to provide the service described above, the electronic device (110) may receive and store various information regarding creator terminals (120-1 to 120-m) and corporate representative terminals (130-1 to 130-n) that have registered as members of the service described above.

[0036] According to embodiments, the electronic device (110) may store profile information, history information, portfolio information, survey response information, platform behavior log information, networking information, etc. of a creator possessing a creator terminal (120-1 to 120-m). According to embodiments, a creator may refer to a person seeking work opportunities, such as employment in a company or participation in a project, as a creator of various cultural and artistic content, such as a video producer, video editor, singer-songwriter, fashion designer, or photographer. Profile information may include name, occupation, career, education, skills, interests, etc. Additionally, history information may include career details, awards, etc., and portfolio information may include content such as projects, works, etc. Additionally, platform behavior log information may include records of activity within the platform, such as post creation history, comment history, and like history. Additionally, networking information may include a friend list, followers, following, etc., within the platform of the aforementioned service. Additionally, the electronic device (110) can obtain survey response information by providing a survey to a creator terminal (120-1 to 120-m) for analyzing the creator's personality and analyzing the survey responses received from the creator terminal (120-1 to 120-m) using a generative language model specialized in a psychological model. The survey response information may include user tendencies, and user tendencies may include multiple personality elements such as extraversion, agreeableness, conscientiousness, emotional stability, and openness. The electronic device (110) can generate the creator's personality information based on multiple personality elements.

[0037] The electronic device (110) can perform data preprocessing on text data of a creator's profile information, history information, portfolio information, survey response information, platform behavior log information, and networking information. Specifically, the electronic device (110) can normalize and refine the text data of each piece of information, tokenize the text data using natural language processing techniques, and extract features such as keywords and topics from the tokenized text data. It will be obvious to a person skilled in the art that preprocessing, including normalization, refinement, tokenization, and feature extraction of text data as described above, can be performed using known techniques.

[0038] The electronic device (110) can receive a file of content created by a creator, i.e., a content file, from a creator terminal (120-1 to 120-m). The creator uploads the content file as their portfolio to the platform of the service of the present disclosure through the creator terminal (120-1 to 120-m), and these contents may be included in portfolio information. According to embodiments, the electronic device (110) can identify the type of content based on the received content file and perform preprocessing on the content data based on the identified type to obtain characteristics of the content components from the content data included in the content file. According to embodiments, the electronic device (110) can perform data preprocessing to obtain characteristics of the components by extracting data to be analyzed from the content data, extracting characteristics of the data to be analyzed, and generating feature information including a plurality of tags for the content and corresponding attribute information based on the extracted characteristics.

[0039] According to the embodiments, the type of content may include video, music, design, or photography. The components of the content serve as elements that form the content and can be used to obtain various characteristics of the content. According to the embodiments, by obtaining characteristics for each component of a single piece of content, feature information of the content can be obtained. Furthermore, the components of the content may be set differently depending on the type of content. For example, if the type of content is music, the components of the content may include beat, melody, timbre, instruments, pitch of the instruments, chorus, and general parts. For example, if the type of content is video, the components of the content may include video purpose, shooting technique, video length, etc. In addition, a person skilled in the art may pre-set appropriate components according to the type of content, without being limited to the examples described above. Furthermore, more components may be set for the content as needed, without being limited to the examples described above; as the number of types of content components increases, the creator's creative style can be analyzed more finely, thereby allowing the requirements of both the creator and the company representative to be reflected more accurately.

[0040] According to embodiments, the electronic device (110) can obtain creator's creative style information based on feature information of each content. The creator's creative style information can be obtained by calculating the similarity between feature information of each content.

[0041] According to the embodiments, the electronic device (110) can store corporate profile information, recruitment information, and survey response information written by a corporate representative corresponding to the corporate representative terminal (130-1 to 130-n). Additionally, the electronic device (110) can collect posts about the company uploaded to a homepage or community on the web (not shown) and news content about the company uploaded to a portal site and perform RAG (Search Augmented Generative) processing. The corporate profile information may include various information such as the company name, business field, and number of employees. Additionally, recruitment information refers to a job posting by a company to hire a content creator and may include information such as the desired content field, preferred career details, and preferred creative style. Furthermore, the electronic device (110) can obtain survey response information by providing a survey to the corporate representative terminal (130-1 to 130-n) to analyze the internal environment of the company and analyzing the survey responses received from the corporate representative terminal (130-1 to 130-n) using a generative language model specialized for corporate analysis models. Survey response information may include information regarding corporate resources, and information regarding corporate resources may include multiple corporate elements such as strategy, structure, systems, shared values, technology, style, and employees. The electronic device (110) may generate internal environment information of the company based on multiple corporate elements.

[0042] The electronic device (110) can perform data preprocessing on text data of recruitment information, posts, news content, and survey response information. Specifically, the electronic device (110) can normalize and refine the text data of each piece of information, tokenize the text data using natural language processing techniques, and extract features such as keywords and topics from the tokenized text data. It will be obvious to a person skilled in the art that preprocessing, including normalization, refinement, tokenization, and feature extraction of text data as described above, can be performed using known techniques.

[0043] The electronic device (110) can obtain information on preferred characteristics and preferred creative styles for the content desired by the company by analyzing data-preprocessed recruitment information, posts, and news content. According to embodiments, the electronic device (110) can obtain information on the type of content desired by the company and characteristics of each component corresponding to the type of content by analyzing keywords and sentences included in corporate profile information, recruitment information, posts, and news content, and can obtain information on the characteristics of the content. According to embodiments, the type of content may include video, music, design, or photography. The components of the content are elements that form the content and can be used to obtain various characteristics of the content. In addition, the components of the content may be set differently depending on the type of content. For example, if the type of content is music, the components of the content may include beat, melody, timbre, instrument, pitch of the instrument, chorus, and general part. For example, if the type of content is video, the components of the content may include video purpose, shooting technique, video length, etc. Furthermore, ordinary technicians are not limited to the examples described above and can pre-configure appropriate components according to the type of content. Additionally, more components can be configured for the content as needed, not limited to the examples described above; as the variety of content components increases, the creator's creative style and the company's preferred creative style can be analyzed in greater detail, thereby allowing the requirements of both the creator and the company representative to be reflected more accurately.

[0044] According to the embodiments, the electronic device (110) can obtain information on a company's preferred creative style based on information on the company's preferred characteristics regarding content. The information on the company's preferred creative style can be obtained by calculating the similarity between the information on the preferred characteristics of each content. Additionally, the electronic device (110) can determine one or more creators that match the company as recommendation information based on the company's preferred characteristics information, the information on the preferred creative style, and the company's internal environment information. Additionally, the electronic device (110) can continuously update a list of company elements including multiple company elements based on the results of analyzing survey responses and the company's feedback information regarding the recommendation information.

[0045] According to the embodiments, the creator terminal (120-1 to 120-m) may be a terminal possessed by a creator who is seeking work opportunities, such as joining a company or participating in a project, or who wishes to interact with other creators. According to the embodiments, the creator may be a creator of various cultural and artistic content, such as a video producer, a video editor, a singer-songwriter, a fashion designer, or a photographer.

[0046] According to the embodiments, the corporate representative terminal (130-1 to 130-n) may be a terminal carried by a person in charge of corporate recruitment or seeking project personnel. The corporate representative terminal (130-1 to 130-n) may transmit a creator recommendation request including a recruitment notice or a project notice to the electronic device (110), and receive a creator determined by the electronic device (110) to correspond to the corporate representative terminal as a recommended creator for the company.

[0047] FIG. 2 is a flowchart relating to a method for performing automatic matching between an AI-based content creator and a company according to embodiments. The method of FIG. 2 can be performed by an electronic device (e.g., the electronic device (110) of FIG. 1, the electronic device (400) of FIG. 4).

[0048] Referring to FIG. 2, in step 201, the electronic device can obtain corporate profile information and recruitment information from a corporate representative's first user terminal (e.g., corporate representative terminal (130-1 to 130-n)).

[0049] According to the embodiments, a company representative may refer to a person responsible for corporate recruitment or seeking project personnel. The company profile information may include various information such as the company name, business sector, and number of employees. Additionally, recruitment information refers to a company job posting or project posting for hiring content creators, and may include information such as the desired content field, preferred experience, and preferred creative style.

[0050] In step 203, the electronic device can collect posts and news content about the company from a plurality of homepages, communities, and portal sites. According to the embodiments, the electronic device can collect posts and news content about the company uploaded to the web according to a preset period. For example, the electronic device can collect posts and news content about the company at a set period as needed, such as one day, one week, etc.

[0051] In step 205, the electronic device can use the first artificial intelligence model to obtain information on the company's preferred characteristics and preferred creative style for the content from the company's recruitment information, posts and news content about the company.

[0052] More specifically, the electronic device can perform data preprocessing on text data included in corporate recruitment information, corporate posts, and news content. The electronic device can normalize and refine the text data of each piece of information, tokenize the text data using natural language processing techniques, and extract features such as keywords and topics from the tokenized text data. It will be obvious to a person skilled in the art that the preprocessing, including normalization, refinement, tokenization, and feature extraction of text data as described above, can be performed using known techniques. According to the embodiments, the electronic device can obtain content preference feature information by using a first artificial intelligence model to obtain the type of content desired by the company and the component-specific features corresponding to the type of content from the recruitment information, posts, and news content.

[0053] According to the embodiments, when the type of content desired by a company is identified in the company's recruitment information, company-related posts, and news content, the electronic device can obtain a plurality of first tags corresponding to a plurality of pre-set tag names for the type of content from a database. That is, the electronic device can identify the type of content desired by the company by analyzing text data and obtain a plurality of first tags corresponding to the type of content. At this time, the tag names may correspond to the components of the content. That is, the electronic device may pre-store a plurality of first tags corresponding to a plurality of components of the content for each type of content in a database. According to the embodiments, the type of content may include at least one of video, music, design, or photography. For example, if the type of content is music, the components of the content may include beat, melody, timbre, instrument, pitch of the instrument, chorus, and general part, and accordingly, the plurality of first tags may include beat, melody, timbre, instrument, pitch of the instrument, chorus, and general part. For example, if the type of content is video, the components of the content may include the purpose of the video, the filming technique, and the length of the video, and accordingly, a plurality of first tags may include the purpose of the video, the filming technique, and the length of the video. In addition, a person skilled in the art is not limited to the examples described above and may pre-set appropriate components and corresponding tag names according to the type of content.

[0054] The electronic device can generate first attribute information corresponding to one or more of the first tags among multiple first tags by extracting features of content preferred by the company from text data of the company's recruitment information, posts about the company, and news content. Unlike content files uploaded by a creator, the company's recruitment information or posts, etc., may not contain attribute information for all of the first tags of the content. The electronic device can analyze one or more attributes of the content preferred by the company by generating embedding vectors corresponding to features corresponding to attribute information for each first tag through keyword and sentence analysis of the text data and inputting them into a first artificial intelligence model. The first artificial intelligence model can be trained to classify which attribute group the features of the content's components belong to based on the attribute values ​​of the set of embedding vectors, and the attribute group output as a classification result can become the attribute information of the corresponding tag. The electronic device can generate first attribute information corresponding to the first tag through such feature extraction, and the first attribute information can correspond to the attribute group based on the attribute values ​​for the first tag.

[0055] According to the embodiments, the first artificial intelligence model may be, for example, one of a deep neural network, a convolutional neural network, a recurrent neural network, a reinforcement learning model, or a machine learning model for classification-regression analysis, and may be implemented using algorithms such as a supervised learning method such as SVM (support vector machine) and a clustering method such as k-NN (k-Nearest Neighbor), but is not limited thereto and may be appropriately selected by a person skilled in the art.

[0056] For example, if the content type is music, job postings or posts may contain only limited information about the content, unlike content files created by a creator; therefore, only attribute information regarding the first tag, such as instruments and beats, may be generated.

[0057] According to embodiments, an electronic device can generate content preference feature information comprising a plurality of first tags and first attribute information corresponding to at least one of the plurality of first tags. Such preference feature information can be obtained for each piece of content identified from text data. Additionally, by calculating the similarity of attribute information by tag between the preference feature information of a company for one or more pieces of content, the electronic device can obtain the company's preferred creative style information based on tags and attribute information where the similarity is greater than or equal to a predetermined value. For example, if it is identified that a predetermined proportion or more of the preference feature information for a specific company's content has identical attribute information for instrument and beat tags, the electronic device determines that the similarity of the attribute information of the instrument and beat tags preferred by the company satisfies a predetermined criterion and can include the identified attribute information of the instrument and beat tags in the company's preferred creative style information. For example, if the preset ratio is 70%, and among the preference feature information for 5 content for a company, the attribute information of the instrument tag in 4 of the preference feature information is piano and the attribute information of the beat tag is medium tempo, then the similarity of the attribute information satisfies the predetermined criteria, so the tag and attribute information can be determined as the company's preferred creative style information.

[0058] In step 207, the electronic device may use a second artificial intelligence model to provide a plurality of surveys to the first user terminal for analyzing the internal environment of the enterprise and receive survey responses for each of the plurality of surveys from the first user terminal. According to embodiments, the electronic device may use a generative language model to provide a plurality of surveys composed of text information in the form of sentences to the first user terminal and receive each survey response composed of text information in the form of sentences from the first user terminal. According to embodiments, the second artificial intelligence model is a generative artificial intelligence model and may be implemented using various types of publicly available large-scale language model APIs. For example, the second artificial intelligence model may be implemented using GPT-4, Claude, LLaMA, Alpaca, etc. GPT-4, Claude, LLaMA, and Alpaca, etc. are composed of a transformer-based decoder structure and operate in a manner that receives text referred to as a command (prompt) and outputs text. Therefore, although omitted from description in this specification, it will be obvious to a person skilled in the art that various processes, such as indexing of sentences and representation as vectors, which are typically performed for data processing through widely known language models, may be additionally performed.

[0059] In step 209, the electronic device can calculate a score for each of a plurality of corporate elements representing the internal environment of the enterprise based on the results of analyzing the received survey responses using the second artificial intelligence model. According to embodiments, the electronic device can identify which of the plurality of corporate elements each survey response contains content about by tokenizing and analyzing the survey responses, which consist of text information in the form of sentences. According to embodiments, the plurality of corporate elements may include corporate resources such as strategy, structure, system, shared values, technology, style, and employees. According to embodiments, strategy refers to means or methods for achieving the organization's long-term plans and goals, and structure may include formal elements (e.g., authority, responsibility) that govern the roles of members and the interrelationships between members. Additionally, system may refer to the organization's management framework, operational procedures, or systems, and shared values ​​may refer to the company's core ideology, values, or purpose. Additionally, technology may include specific elements necessary for executing the strategy, such as techniques regarding equipment or process operation, sales capabilities, marketing capabilities, employee motivation, and various management techniques utilized in organizational operations. Furthermore, "style" refers to the management or leadership style of the manager leading the organization, while "employees" can refer to the workforce composition within the organization. In other words, for each survey response from a corporate representative, the electronic device identifies which corporate element—strategy, structure, systems, shared values, technology, style, or employees—the response relates to, and can generate corporate characteristics for that element. Multiple corporate characteristics can be pre-set for each corporate element, and the electronic device can determine which corporate characteristic a given corporate element possesses. For example, in the case of the corporate element "style," the electronic device can determine that the corresponding corporate element is one of multiple corporate characteristics, such as democratic, autocratic, or laissez-faire. The corporate characteristics described above are merely illustrative examples and are not limited thereto.

[0060] In step 211, the electronic device can generate internal environment information of the enterprise based on enterprise characteristics for each of the plurality of personality elements. The internal environment information may include the names of the plurality of enterprise elements and enterprise characteristics generated for each of the plurality of enterprise elements.

[0061] In step 213, the electronic device may store information regarding the company's preferred characteristics, preferred creative style, and internal environment of the company in the electronic device's database in association with the company's profile information. The information regarding the company's preferred characteristics, preferred creative style, and internal environment is as described in steps 205 and 211. According to the embodiments, the company's profile information may include various information such as the company name, business sector, and number of employees.

[0062] In step 215, the electronic device can determine a content creator that matches the company as recommendation information based on the company's preferred characteristic information, preferred creative style information, and internal environment information.

[0063] According to the embodiments, a content creator matching the company's recruitment information can be determined based on the electronic company's preferred characteristic information, preferred creative style information, and internal environment information. The electronic device can determine the characteristic information of each piece of content created by the content creator, the creator's creative style information, and the personality information by performing an analysis of the creator's portfolio information and personality information uploaded to the platform. The electronic device can perform matching based on known similarity calculations and graph theory. In this case, the electronic device can pre-store data regarding personality information corresponding to each piece of internal environment information in a database. Accordingly, the electronic device can set the company and the creator as nodes, respectively, and perform creator-company matching by calculating the similarity between the characteristic information, creative style information, and personality information of each piece of content of the creator, and the personality information corresponding to the preferred characteristic information, preferred creative style information, and internal environment information in the recruitment information and project announcements.

[0064] In step 217, the electronic device may provide the determined recommendation information to the first user terminal. That is, the electronic device may transmit a content creator matched with the company as recommendation information to the first user terminal held by the company representative.

[0065] In step 219, the electronic device can update a list of corporate elements including multiple corporate elements representing the internal environment of the company based on the results of analyzing survey responses and feedback information on recommendation information.

[0066] According to the embodiments, the electronic device can identify that the survey response contains content regarding a corporate element different from a plurality of corporate elements based on analyzing text information in the form of sentences constituting the survey response. Additionally, the electronic device can obtain the corporate element output as a result of clustering by performing AI-based clustering based on the identification of content regarding a different corporate element. According to the embodiments, the electronic device can receive feedback information regarding recommendation information from a first user terminal and, based on the feedback information, identify a corporate element among a plurality of corporate elements that exhibits a similarity level below a predetermined threshold with respect to the recommendation information. Additionally, if a plurality of feedback information is received in which the identified corporate element exhibits a similarity level below a predetermined threshold, the electronic device can determine the identified corporate element as a corporate element to be discarded. According to the embodiments, the electronic device can update the corporate element list based on at least one of adding the corporate element output as a result of clustering to the corporate element list or discarding the corporate element to be discarded from the corporate element list.

[0067] According to the embodiments, when the electronic device analyzes text information in the form of sentences constituting the survey response in step 209, it can identify from the result that the response contains content regarding a corporate element different from a plurality of pre-set corporate elements. The database of the electronic device may store not only the names of the plurality of pre-set corporate elements but also various corporate element names, and may store a large dataset of keywords corresponding to each corporate element. Through this, the electronic device can identify cases where content regarding a corporate element other than the plurality of pre-set corporate elements is included in the survey response. According to the embodiments, the electronic device can obtain the corporate element output as a result of clustering by performing AI-based clustering based on the identification of content regarding a different corporate element. That is, if the survey response contains content regarding a corporate element other than the plurality of pre-set corporate elements, the electronic device may wait for statistical processing until survey response data containing that other corporate element is accumulated. When a sufficient amount of survey response data is accumulated, the electronic device may determine that other personality element as a new corporate element to be added to the personality element list and add it to the corporate element list. For example, if multiple pre-set corporate elements are strategy, structure, systems, shared values, and technology, information regarding other corporate elements, such as style and employees, in addition to these elements may be identified in the survey responses. These other corporate elements can be added to the list of corporate elements once a sufficient amount of data is accumulated.

[0068] According to the embodiments, the electronic device may receive feedback information from the first user terminal regarding the recommendation information provided in step 217. The feedback information may include text information in the form of sentences. If there is a content creator among the recommendation information that a company determines was not suitable for hiring, the electronic device may receive from the first user terminal the reason why the company determined the recommendation information was not suitable in the form of a sentence. The electronic device may analyze the text information in the form of sentences constituting the feedback information to extract company elements that received negative feedback from the feedback information, and may identify the extracted company elements as having a similarity level below a predetermined standard with respect to the recommendation information. According to the embodiments, the electronic device may obtain company elements output as a result of clustering by performing AI-based clustering based on the identification of company elements that have a similarity level below a predetermined standard. That is, the electronic device may wait for feedback information including company elements that received negative feedback to accumulate for statistical processing. When a sufficient amount of feedback information is accumulated, the electronic device may determine that the company element is not suitable for consideration in matching and determine it as a company element to be discarded from the list of company elements. For example, if multiple pre-configured corporate elements are strategy, structure, system, shared value, and technology, negative feedback regarding the system can be identified in the feedback information. If a sufficient amount of negative feedback information regarding the system accumulates, the electronic device may determine that the element is not important for the system to perform matching and discard it from the list of corporate elements.

[0069] FIG. 3 is an example diagram regarding the update of a list of corporate elements according to embodiments.

[0070] Referring to FIG. 3, the electronic device can generate internal environment information of a company based on a list of corporate elements (310) composed of a plurality of preset corporate elements A, B, C, D, E, and F, and provide recommendation information that matches the company. If the electronic device analyzes the survey response received from the user terminal of a company representative, the electronic device can identify that the survey response contains content regarding corporate element G that is not included in the list of corporate elements (310). The electronic device accumulates the survey response data containing content regarding corporate element G whenever it receives it, and when a predetermined amount of survey response data is accumulated, the electronic device can add corporate element G to the list of corporate elements. Accordingly, the list of corporate elements (310) can be updated to a list of corporate elements (320) containing a plurality of corporate elements A, B, C, D, E, F, and G.

[0071] Meanwhile, the electronic device may receive feedback information after providing recommendation information to the user terminal. At this time, the feedback information may include negative feedback regarding corporate element D. The electronic device may identify that there is negative feedback regarding corporate element D in the feedback information and may accumulate feedback information containing negative feedback regarding corporate element D whenever it receives it. When a predetermined amount of feedback information is accumulated, the electronic device may determine that corporate element D is not suitable for consideration in matching and may discard it from the corporate element list. Accordingly, the corporate element list (310) may be updated to a corporate element list (330) including multiple corporate elements A, B, C, E, and F.

[0072] Meanwhile, the electronic device may receive both survey responses containing content regarding corporate element G, which is not included in the corporate element list (310), and feedback information containing negative feedback regarding corporate element D. In this case, the electronic device may accumulate the survey response data containing content regarding corporate element G and the feedback information containing negative feedback regarding corporate element D whenever it receives them. When a predetermined amount of information is accumulated, the electronic device may add corporate element G to the corporate element list and discard corporate element D. Accordingly, the corporate element list (310) may be updated to a corporate element list (340) containing multiple corporate elements A, B, C, E, F, and G.

[0073] In this way, the present invention can customize the list of corporate elements for more accurate matching by continuously updating the list of corporate elements through the extraction of corporate elements that may become new consideration factors and corporate elements that may not be considered suitable for matching factors from survey responses and feedback information, in the matching between content creators and companies.

[0074] FIG. 4 is a configuration diagram of an electronic device according to embodiments of the present invention. The electronic device (400) may be included in the electronic device (110) of the system (100 of FIG. 1) for performing automatic matching between an artificial intelligence-based content creator and a company according to the present invention, or the electronic device (110) may be included in the electronic device (400).

[0075] Referring to FIG. 4, the electronic device (400) may include a transceiver (410), a processor (420), and a memory (430). FIG. 4 illustrates only the components of the electronic device (400) related to the embodiment of the present disclosure. Therefore, it will be understood by those skilled in the art related to the present embodiment that other general components may be included in the electronic device in addition to the components illustrated in FIG. 4.

[0076] The transceiver (410) can establish a communication channel with an external device (e.g., creator terminal, corporate representative terminal, etc.) and transmit and receive various data with the external device. The transceiver (410) can transmit and receive relevant information by performing wired / wireless communication. The communication technologies used by the transceiver (410) may include, but are not limited to, GSM (Global System for Mobile communication), CDMA (Code Division Multi Access), LTE (Long Term Evolution), 5G, WLAN (Wireless LAN), Wi-Fi (Wireless-Fidelity), Bluetooth (Bluetooth™), RFID (Radio Frequency Identification), Infrared Data Association (IrDA), ZigBee, NFC (Near Field Communication), etc.

[0077] The processor (420) can control the overall operation of the electronic device (400) and process data and signals. The processor (420) may be composed of at least one hardware unit. Additionally, the processor (420) may operate by one or more software modules generated by executing program code stored in memory (430). The processor (420) can control the overall operation of the electronic device (400) and process data and signals by executing computer programs or instructions stored in memory (430). The processor (420) may be configured to perform the contents of the artificial intelligence-based automatic matching method between content creators and companies described throughout this disclosure.

[0078] The memory (430) may store program code and information necessary to execute a computer program for performing the method of performing automatic matching between an AI-based content creator and an enterprise described throughout the present disclosure. The memory (430) may be volatile memory or non-volatile memory.

[0079] The database (440) can store various information. The database (440) can store multiple artificial intelligence models used to generate corporate preference feature information, provide surveys, and receive and analyze survey responses under the control of the processor (420), and can store various data collected from websites, communities, etc. Additionally, the database (440) can store training data for training these artificial intelligence models.

[0080] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using one or more general-purpose or special-purpose computers, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and one or more software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. Additionally, other processing configurations, such as parallel processors, are also possible.

[0081] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination. The program instructions recorded on the medium may be those specifically designed and configured for the embodiment, or they may be those known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

[0082] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, computer storage medium or device, or transmitted signal wave so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on one or more computer-readable recording media.

[0083] Although the embodiments have been described above with reference to the limited drawings, those skilled in the art can apply various technical modifications and variations based on the above. For example, suitable results may be achieved even if the described techniques are performed in a different order than described, and / or if the components of the described system, structure, device, circuit, etc. are combined or assembled in a form different from described, or replaced or substituted by other components or equivalents.

[0084] Therefore, other implementations, other embodiments, and equivalents to the claims also fall within the scope of the claims set forth below.

Claims

1. An artificial intelligence-based automatic matching method between content creators and companies performed by an electronic device, wherein A step of obtaining corporate profile information and recruitment information from a first user terminal of a corporate representative; A step of collecting posts and news content regarding the said company from multiple homepages, communities, and portal sites; A step of obtaining information on the company's preferred characteristics and preferred creative style regarding the content from the company's recruitment information, posts and news content regarding the company, using a first artificial intelligence model; A step of using a second artificial intelligence model to provide a plurality of surveys for analyzing the internal environment of the company to the first user terminal, and receiving survey responses for each of the plurality of surveys from the first user terminal; A step of generating corporate characteristics for each of a plurality of corporate elements representing the internal environment of the company, based on the results of analyzing the received survey responses using the second artificial intelligence model; A step of generating internal environment information of the company based on the corporate characteristics for each of the plurality of corporate elements mentioned above; A step of associating the company’s preference feature information regarding the content, the company’s preference creative style information, and the company’s internal environment information with the profile information and storing them in the database of the electronic device; A step of determining a content creator matched with the company as recommendation information based on the above-mentioned preferred feature information, the above-mentioned preferred creation style information, and the above-mentioned internal environment information; A step of providing the above-determined recommendation information to the first user terminal; and A method comprising the step of updating a list of corporate elements including the plurality of corporate elements based on the results of analyzing the above survey responses and feedback information regarding the above recommendation information.

2. In Paragraph 1, The preference feature information of the above-mentioned company is obtained by analyzing features extracted from content identified in the company's recruitment information, posts and news content regarding the company, and The above-mentioned preferred creative style information is obtained based on calculating the similarity of preferred feature information for one or more contents.

3. In Paragraph 2, The survey response for each of the plurality of surveys received from the first user terminal is composed of text information in the form of a sentence, and A method for identifying which of the plurality of corporate elements each survey response contains content about based on the analysis of the above-mentioned sentence-form text information.

4. In Paragraph 3, A step of identifying, based on the analysis of the text information in the form of the above sentence, that the survey response contains content regarding a corporate element different from the plurality of corporate elements; and A method further comprising the step of obtaining a corporate element output as a result of said clustering by performing AI-based clustering based on the identification of the content regarding the different corporate elements above.

5. In Paragraph 4, A step of receiving feedback information regarding the recommendation information from the first user terminal; A step of identifying a company element among the plurality of company elements that exhibits a similarity level below a predetermined standard with respect to the recommendation information based on the feedback information; and A method further comprising the step of determining the identified corporate element as a corporate element to be discarded when a plurality of feedback information is received indicating that the identified corporate element has a similarity level below a predetermined standard.

Images