KR20210107473A - System for providing story contents platfrom service with distribution of revenue between creator and various participants - Google Patents

Abstract

The present invention provides a story content platform service providing system for distributing profits to a creator and multiple participants which can induce enthusiastic translation and correction. The story content platform service providing system for distributing profits to a creator and multiple participants comprises: a creator terminal providing story content, and receiving profits for a secondary work and royalties of the provided story content; a translator terminal translating text included in the story content, and receiving advertisement profits generated as the translated story content is consumed; a correction terminal correcting a portion or the entirety of the text translated by the translator terminal, and receiving the advertisement profits in proportion to a corrected ratio; and a content platform service providing server including a storage unit mapping the story content received from the creator terminal and the creator terminal to build a database, an artificial intelligence translation unit translating and distributing the story content in the language of each country by using a previously stored real-time translation program, a management unit mapping and storing the translator terminal and translation text if the story content translated by the artificial intelligence translation unit or the story content of the storage unit is translated by the translator terminal, and a distribution unit executing profit distribution in proportion to the corrected ratio if the translation text or the story content translated by the artificial intelligence translation unit is corrected by the correction terminal.

Description

SYSTEM FOR PROVIDING STORY CONTENTS PLATFROM SERVICE WITH DISTRIBUTION OF REVENUE BETWEEN CREATOR AND VARIOUS PARTICIPANTS

The present invention relates to a story content platform service providing system that distributes revenue to creators and multiple participants, and not only creators but also translators and reviewers who have processed story content into a form that can be consumed by users around the world, including advertising revenue and secondary works It provides a platform for distributing profits.

With the development of new media-based digital platforms, the value chain system of the content industry is also changing. As a result, the status of content creators in the form of one-person creatives and one-person media in various fields is rising, and there are also relay operators that link consumers, creators, and advertisers on new media platforms, such as MCN (Multi-Channel Network) operators. This change is due to the fact that new types of content are emerging as consumers' media use of content is diversifying, centering on video platforms such as YouTube, social platforms, and Netflix, and mobile media. In Korea, studies on the MCN model are also being conducted from the viewpoint of content business. There are opinions that point out that there is.

At this time, authoring and profit sharing methods for digital works have been researched and developed. A configuration that determines the degree of contribution indicating the degree of contribution to the production of a digital work, a configuration that provides a service to consumers based on the determined contribution, and a configuration that distributes the revenue generated from the serviced digital work to the participants based on the contribution Including, participants include authors and translators of original works, voice actors who create sound files from original works, background music articles that insert background music into sound files, sound effects articles that insert sound effects into sound files, and digital works trading platform A configuration is disclosed comprising a platform provider that provides have.

However, the MCN business is a creator-centered atypical digital content business, which ties individual creators to a network, provides them with various support necessary for production, and is defined as a business that generates profits by using creator content. Creators' advertising income is not large enough to continuously reinvest in content production, and in order for early creators to systematically produce content and grow channel influence, it is necessary to recognize creators as an important industry field, and to take a policy approach and build infrastructure. do. In addition, when MCN is defined as a business that provides all or part of a creator's content planning, production, marketing, copyright, distribution, and business, MCN is defined as a company that provides customer development, promotion, branding strategy development, revenue generation, Content creation, digital rights management and legal services, collaboration, etc. are prerequisites. Accordingly, research and development of a platform that distributes profits while multi-collaborators participate is required.

In one embodiment of the present invention, anyone, regardless of age or sex, can upload and share their story on a story platform, and provide real-time artificial intelligence translation of story text so that subscribers in each country can access stories from around the world. In addition, the story content is translated directly by a translator who translates the story into each language, or awkward expressions are shared in a way that is corrected by the reviser through simple mechanical substitution with artificial intelligence translation, and at the same time, Ratings are given based on reviews or ratings, and revenue is distributed based on the contribution to translation and correction, and when story content is produced, published, or derived as a derivative work, the revenue is also distributed to multiple participants. In addition, it is possible to provide a method of providing a story content platform service that distributes revenue to creators and multiple participants, so that even the translators and revisers who helped the box office can receive a fair share of revenue, and can induce active translation and correction. have. However, the technical task to be achieved by the present embodiment is not limited to the technical task as described above, and other technical tasks may exist.

As a technical means for achieving the above-described technical problem, an embodiment of the present invention provides a story content, a creator terminal receiving a distribution of the copyright fee of the provided story content and revenue for a secondary work, text included in the story content Translator terminal, which receives advertising revenue generated by the consumption of translated story content, and a modified terminal and creator who correct some or all of the translated text in the translator terminal, and receive advertising revenue distributed in proportion to the modified ratio The storage unit that maps the story content received from the terminal and the creator's terminal into a database, the artificial intelligence translation unit that translates and distributes the story content into the language of each country using a pre-stored real-time translation program, When the story content or the story content of the storage is translated by the translator terminal, the management unit that maps and stores the translator terminal and the translated text, or the artificial intelligence translation unit in the correction terminal, the translated story content or the translated text is corrected at the modified rate. It includes a content platform service providing server including a distribution unit that performs profit distribution in proportion.

According to any one of the above-described problem solving means of the present invention, anyone, regardless of age or sex, can upload and share their story on the story platform, and provide real-time artificial intelligence translation of the story text, so that subscribers in each country can of the story, and the story content is directly translated by a translator who translates the story into the language of each country, or awkward expressions are shared in a way that is corrected by a modifier through simple mechanical substitution with artificial intelligence translation; At the same time, ratings are given by reviews or ratings for translation and correction, and revenue is distributed based on the contribution to translation and correction, and when story content is produced, published, or derived as a derivative work, the revenue is also distributed to multiple participants. By distributing all of them, not only the original copyright holder but also the translators and revisers who helped the box office can receive a fair share of revenue and induce active translation and correction.

1 is a view for explaining a story content platform service providing system for distributing revenue to creators and multiple participants according to an embodiment of the present invention.
FIG. 2 is a block diagram illustrating a content platform service providing server included in the system of FIG. 1 .
3 and 4 are diagrams for explaining an embodiment in which a story content platform service for distributing revenue to creators and multiple participants according to an embodiment of the present invention is implemented.
5 is an operation flowchart illustrating a method of providing a story content platform service for distributing revenue to creators and multiple participants according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art can easily implement them. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. And in order to clearly explain the present invention in the drawings, parts irrelevant to the description are omitted, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. . Also, when a part "includes" a component, it means that other components may be further included, rather than excluding other components, unless otherwise stated, and one or more other features However, it is to be understood that the existence or addition of numbers, steps, operations, components, parts, or combinations thereof is not precluded in advance.

The terms "about", "substantially", etc. to the extent used throughout the specification are used in a sense at or close to the numerical value when the manufacturing and material tolerances inherent in the stated meaning are presented, and serve to enhance the understanding of the present invention. To help, precise or absolute figures are used to prevent unfair use by unscrupulous infringers of the stated disclosure. As used throughout the specification of the present invention, the term “step for (to)” or “step for” does not mean “step for”.

In this specification, a "part" includes a unit realized by hardware, a unit realized by software, and a unit realized using both. In addition, one unit may be implemented using two or more hardware, and two or more units may be implemented by one hardware.

In this specification, some of the operations or functions described as being performed by the terminal, apparatus, or device may be performed instead of in a server connected to the terminal, apparatus, or device. Similarly, some of the operations or functions described as being performed by the server may also be performed in a terminal, apparatus, or device connected to the server.

In this specification, some of the operations or functions described as mapping or matching with the terminal means mapping or matching the terminal's unique number or personal identification information, which is the identification data of the terminal. can be interpreted as

Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

1 is a view for explaining a story content platform service providing system for distributing revenue to creators and multiple participants according to an embodiment of the present invention. 1, the story content platform service providing system 1 that distributes revenue to creators and multiple participants includes at least one creator terminal 100, a content platform service providing server 300, and at least one translator terminal ( 400), and at least one modification terminal 500 may be included. However, since the story content platform service providing system 1 for distributing revenue to the creator and multiple participants of FIG. 1 is only one embodiment of the present invention, the present invention is not limitedly interpreted through FIG. 1 .

In this case, each component of FIG. 1 is generally connected through a network 200 . For example, as shown in FIG. 1 , at least one creator terminal 100 may be connected to the content platform service providing server 300 through the network 200 . In addition, the content platform service providing server 300 may be connected to at least one creator terminal 100 , at least one translator terminal 400 , and at least one correction terminal 500 through the network 200 . In addition, the at least one translator terminal 400 may be connected to the content platform service providing server 300 through the network 200 . In addition, the at least one correction terminal 500 may be connected to the at least one creator terminal 100 , the content platform service providing server 300 , and the at least one translator terminal 400 through the network 200 .

Here, the network refers to a connection structure in which information exchange is possible between each node, such as a plurality of terminals and servers, and an example of such a network includes RF, 3rd Generation Partnership Project (3GPP) network, Long Term (LTE). Evolution) network, 5th Generation Partnership Project (5GPP) network, WIMAX (World Interoperability for Microwave Access) network, Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network) , PAN (Personal Area Network), Bluetooth (Bluetooth) network, NFC network, satellite broadcasting network, analog broadcasting network, DMB (Digital Multimedia Broadcasting) network, and the like are included, but are not limited thereto.

In the following, the term at least one is defined as a term including the singular and the plural, and even if at least one term does not exist, each element may exist in the singular or plural, and may mean the singular or plural. it will be self-evident In addition, that each component is provided in singular or plural may be changed according to embodiments.

At least one creator terminal 100 may be a terminal for uploading story content using a web page, an app page, a program or an application related to a story content platform service that distributes revenue to creators and multiple participants. In addition, the at least one creator terminal 100 may be a terminal that receives or receives a copyright fee or revenue for the story content from the content platform service providing server 300 . The at least one creator terminal 100 may be a terminal to which a rating or level is given by a rating or review such as recommendation or non-recommendation within the platform of the content platform service providing server 300 .

Here, the at least one creator terminal 100 may be implemented as a computer that can access a remote server or terminal through a network. Here, the computer may include, for example, a navigation device, a laptop computer equipped with a web browser, a desktop computer, and a laptop computer. In this case, the at least one creator terminal 100 may be implemented as a terminal capable of accessing a remote server or terminal through a network. At least one creator terminal 100 is, for example, as a wireless communication device that ensures portability and mobility, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS(Personal Handyphone System), PDA(Personal Digital Assistant), IMT(International Mobile Telecommunication)-2000, CDMA(Code Division Multiple Access)-2000, W-CDMA(W-Code Division Multiple Access), Wibro(Wireless Broadband Internet) ) terminal, a smart phone, a smart pad, a tablet PC, etc. may include all kinds of handheld-based wireless communication devices.

The content platform service providing server 300 may be a server that provides a story content platform service web page, app page, program or application that distributes revenue to creators and multiple participants. In addition, the content platform service providing server 300 may be a server that collects story content from at least one creator terminal 100 , maps it with the creator terminal 100 , and stores it. In addition, the content platform service providing server 300 may be a server that uploads story content by translating it into each language in real time with a pre-stored artificial intelligence translation program. In addition, the content platform service providing server 300, when the story content is translated by at least one translator terminal 400, uploads the translated story content, and stores ratings or reviews such as recommendation or non-recommendation as a log. can be In addition, the content platform service providing server 300 uploads the final version reflecting the correction when a correction operation is made on the translated story content in at least one of the correction terminals 500 , and recommends or not recommends the corrected story content. It may be a server that stores ratings or reviews such as logs as logs. In addition, the content platform service providing server 300 may be a server that assigns a rating for translation and correction based on a rating or review for translation or correction, and distributes revenue based on contribution. In addition, the content platform service providing server 300 may be a server that distributes and settles revenue when story content is published or produced or derived as a secondary work.

Here, the content platform service providing server 300 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, a navigation device, a laptop computer equipped with a web browser, a desktop computer, and a laptop computer.

The at least one translator terminal 400 may be a translator's terminal using a web page, an app page, a program or an application related to a story content platform service that distributes revenue to creators and multiple participants. In this case, the at least one translator terminal 400 may be a translator's terminal that directly translates the story content provided by the content platform service providing server 300 or re-translates the story content translated with a pre-stored artificial intelligence translation program. . In addition, the translator terminal 400 may be a terminal that receives a translator rating from the content platform service providing server 300 according to a review or rating of the translated story content.

Here, the at least one translator terminal 400 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, a navigation device, a laptop computer equipped with a web browser, a desktop computer, and a laptop computer. In this case, the at least one translator terminal 400 may be implemented as a terminal capable of accessing a remote server or terminal through a network. At least one translator terminal 400, for example, as a wireless communication device that guarantees portability and mobility, navigation, PCS (Personal Communication System), GSM (Global System for Mobile communications), PDC (Personal Digital Cellular), PHS(Personal Handyphone System), PDA(Personal Digital Assistant), IMT(International Mobile Telecommunication)-2000, CDMA(Code Division Multiple Access)-2000, W-CDMA(W-Code Division Multiple Access), Wibro(Wireless Broadband Internet) ) terminal, a smart phone, a smart pad, a tablet PC, etc. may include all kinds of handheld-based wireless communication devices.

At least one modification terminal 500 is a story content or translator terminal 400 translated into an artificial intelligence program using a web page, app page, program or application related to a story content platform service that distributes revenue to creators and multiple participants. It may be a terminal for editing the translated story content. In addition, the at least one modified terminal 500 may be a terminal capable of receiving revenue distribution according to a modified ratio, that is, a contribution level, and being given a rating by a review or rating. The ratio of receiving revenue may be contribution, but it may also depend on the result of a complex calculation such as the ratio of the edited text or the rating.

Here, the at least one modification terminal 500 may be implemented as a computer capable of accessing a remote server or terminal through a network. Here, the computer may include, for example, a navigation device, a laptop computer equipped with a web browser, a desktop computer, and a laptop computer. In this case, the at least one modified terminal 500 may be implemented as a terminal capable of accessing a remote server or terminal through a network. The at least one modified terminal 500 is, for example, a wireless communication device that ensures portability and mobility, including navigation, Personal Communication System (PCS), Global System for Mobile communications (GSM), Personal Digital Cellular (PDC), PHS(Personal Handyphone System), PDA(Personal Digital Assistant), IMT(International Mobile Telecommunication)-2000, CDMA(Code Division Multiple Access)-2000, W-CDMA(W-Code Division Multiple Access), Wibro(Wireless Broadband Internet) ) terminal, a smart phone, a smart pad, a tablet PC, etc. may include all kinds of handheld-based wireless communication devices.

2 is a block diagram for explaining a content platform service providing server included in the system of FIG. 1, and FIG. 3 is a story content platform service that distributes revenue to creators and multiple participants according to an embodiment of the present invention. It is a diagram for explaining an embodiment.

Referring to FIG. 2 , the content platform service providing server 300 includes a storage unit 310 , a translation unit 320 , a management unit 330 , a distribution unit 340 , a rating unit 350 , a display unit 360 , It may include a creation unit 370 and a distribution unit 380 .

At least one creator terminal 100, at least one translator terminal 400, and at least one When transmitting a story content platform service application, program, app page, web page, etc. that distributes revenue to creators and multiple participants to the correction terminal 500, at least one creator terminal 100, at least one translator terminal 400 ), and at least one modification terminal 500 may install or open a story content platform service application, program, app page, web page, etc. that distributes revenue to creators and multiple participants. In addition, the service program may be driven in at least one creator terminal 100 , at least one translator terminal 400 , and at least one correction terminal 500 by using a script executed in a web browser. Here, the web browser is a program that enables the use of a web (WWW: world wide web) service, and refers to a program that receives and displays hypertext written in HTML (hyper text mark-up language), for example, Netscape , Explorer, Chrome, and the like. In addition, the application means an application on the terminal, for example, includes an app (app) executed in a mobile terminal (smartphone).

Referring to FIG. 2 , the storage unit 310 may map the story content received from the creator terminal 100 and the creator terminal 100 to form a database. In this case, the storage unit 310 may upload the story content on a page provided by the content platform service providing server 300 . In this case, the creator terminal 100 may provide the story content, and receive a distribution of the copyright fee of the provided story content and the revenue for the secondary work.

The artificial intelligence translation unit 320 may translate and distribute the story content into the language of each country using a pre-stored real-time translation program. In this case, the artificial intelligence translation unit 320 may further provide a virtualization service so that the user or each terminal of the user is translated in real time into the native language. For example, computer virtualization and the cloud can be used to make up for the lack of infrastructure. The first is Iaas (Infrastructure as a Service), which can provide various infrastructure resources such as server resources, IP, network, storage, and power required for server operation flexibly and quickly. Iaas can easily add or remove resources and provide an operating system so a friendly environment can be given. Second, the service can be provided as Paas (Platform as a Service), which provides a stable environment and an API for developing applications using the environment. Paas can easily build and distribute source code, and it is easy to scale out according to usage. Third, SaaS (Software as a Service) is a service that provides users with application programs running in the cloud environment. Saas can be easily accessed from anywhere on the Internet, and can be accessed from anywhere with a web browser. At this time, depending on the requirements of the factory, Baas (Backend as a Service) may be further added. Baas is a service specialized for mobile applications and can provide server-side applications such as member management, push, and file processing that are difficult to process in mobile applications. The platform of Paas can be used and the provided backend module can be configured so that it can be used directly through REST API or library CALL.

In this case, the artificial intelligence translation unit 320 may translate in real time using a Neural Machine Translation model using a neural network or a pre-stored Corpus-based Statistical Machine Translation model. Here, the artificial intelligence translation unit 320, when using a machine translation model using a neural network, uses a multi-lingual corpus for the learning process, and uses a first language in the spoken language translation domain. Can be translated into a second language.

To this end, a preprocessing process is firstly executed, and word segmentation processing may be performed using a word analyzer suitable for language characteristics of each country. For example, a Korean sentence may use a Komoran morpheme analyzer, an English sentence may use Moses Tokenizer, a Japanese sentence may use a Mecab Japanese morpheme analyzer, and a Chinese sentence may use a Stanford Chinese Word Segmenter, but is not limited thereto. In addition, in the case of English sentences, true-casing (case normalization) can be performed on all sentences by learning the Moses true-casing model as a learning corpus. In order to use the multi-language resource, a target language token may be added to the beginning of a source sentence, for example, Korean-Japanese parallel data may be used.

The second is a step of expressing a subword. The NMT model generally uses a fixed-size word dictionary. Considering that machine translation is an Open Vocabulary Problem due to formats such as names, numbers, and dates, using a fixed-size word dictionary is difficult Out-of-vocabulary) words cannot be expressed. As a way to alleviate the OOV problem, a dictionary can be constructed by expressing words in smaller units and sub-words. The subword expression method may be, for example, Byte-pair Encoding (BPE), Word-piece Model (WPM), or the like, but is not limited thereto.

After the pre-processing and expression are completed, thirdly, learning and evaluation must be performed. The learning data and evaluation data can be composed of pre-stored Korean-English parallel corpus, Korean-Chinese parallel corpus, Korean-Japanese parallel corpus, etc. can In this case, as the data, a script of a lecturer containing various topics used in at least one lecture may be used. Because the speaker speaks colloquially, a more natural colloquial translation is possible. Of course, a written language such as news can be used, and in this case, the difficulty of translation is lower because standardized data can be used rather than colloquially translated. Meanwhile, in addition to the lecture data described above, in order to improve the performance of the translation model, other corpora may be further used, but the type is not limited. In addition, since various translation models may be used in addition to the above-described translation model, the present invention is not limited to the above-described translation model and is not excluded for reasons not listed.

When the translator terminal 400 translates the story content translated by the artificial intelligence translation unit or the story content of the storage unit, the management unit 330 may map and store the translated text with the translator terminal 400 . In this case, the translator terminal 400 may translate the text included in the story content, and receive advertising revenue generated while the translated story content is consumed. The profit distribution basis will be described later in the distribution unit 340 .

The distribution unit 340 may perform revenue distribution in proportion to the corrected ratio when the story content or the translated text translated by the artificial intelligence translation unit is corrected in the correction terminal 500 . The correction terminal 500 may correct some or all of the text translated by the translator terminal 400 and receive advertising revenue distributed in proportion to the corrected ratio.

In this case, the revenue may be advertising revenue, but is not limited thereto, and may be revenue for secondary works to be described later. In addition, the distribution unit 340 collects a unit or real-time log in which the translated story content of the translation and correction terminal 500 of the translator terminal 400 is consumed, and a log generated whenever a work is sold online. Also, it is possible to verify settlement and distribution by standardizing logs generated when end users use works. For example, since the format of the log used for each right holder and company is different, it takes considerable cost and time to verify settlement and distribution through the log. In order to solve this problem, it can be solved with a system using logs that standardizes logs and integrates and analyzes standardized logs for settlement verification through the corresponding logs. This integrated log system automatically collects and analyzes view logs, upload logs, sales history logs, actual transaction history databases, and settlement logs that may actually occur in consuming or transacting copyrighted works in real time, and compares and analyzes them in reality This can be resolved by enhancing trust in the settlement through

In addition, in case of omission of settlement, non-affiliation, non-call of filtering, intentional omission, etc. that cause omission of settlement, etc. are aggregated in real time, analyzed and recorded, thereby providing considerable information to make settlement transparent. As a measure to solve the lack of trust in settlement due to the absence of a verification system for settlement and distribution, settlement verification is possible through settlement analysis service through big data.

When the distribution unit 340 monitors the usage status of the user terminal to calculate the copyright usage fee and distributes and settles the revenue, the distribution unit 340 calculates the copyright usage fee based on at least one factor constituting the usage status and calculates the copyright usage rights. , at least one factor, and copyright usage fees may be stored as a history log. In addition, when the work is an animation work, the distribution unit 340 automatically collects real-time logs, including upload sales log, filtering log, actual transaction log, real-time settlement log, and non-affiliate monitoring log, and collects the collected data The number of missing settlements can be counted in real time by comparing the automatically collected real-time logs and the settlement details on the sharing platform (not shown), and automatically analyze logs by item. The number of errors or omissions can be sent back to each party to request feedback, thereby building mutual trust.

At this time, the real-time log automatically collected from the sharing platform (not shown) automatically collects real-time collection logs, such as upload sales log, filtering log, real transaction log, real-time settlement log, non-affiliate monitoring and verification log, and collects the collected data. Real-time automatic matching is possible by organizing by unique key criteria. In order to analyze real-time logs, the results of non-affiliation cause analysis, filtering non-calls, intentional omissions, non-affiliation downloads, and omissions of settlement are aggregated in real time according to a logic designed in advance in consideration of the characteristics of each log, and automatically for each item. A method of analyzing the log may be used. And, to collect the settlement data, it can be used as a value to be automatically stored and analyzed by comparison with the data of the sharing platform by automatically storing the log of settlement data delivered in real time or monthly. Of course, it will be obvious that the collected log, reference value, and comparison value are not limited to the above-described log, and may be changed according to the type of contract or the free intention between signatures or embodiments.

The rating unit 350 counts the number of recommendations and the number of non-recommendations for the translation or correction of the story content translated or corrected in the translator terminal 400 or the correction terminal 500, and based on the counted number of recommendations and non-recommendations, the translator terminal (400) or the modified terminal 500 may be assigned a grade, and revenue distribution may be performed based on the granted grade. Here, the number of recommendations and the number of non-recommendations are good for analyzing quantitative data, but not suitable for analyzing qualitative data. For example, one recommendation and one non-recommendation are given when translator A translates accurately according to the native language and when the translation is close to machine translation. However, in order to give a grade in that degree, you can find out how badly translated and how well it is translated by looking at the review. Scores can be calculated, and Sentiment Dictionary Builder, which builds a dictionary by analyzing profanity, slang, and abbreviations through a lexical analyzer and machine learning, can be used. Based on this, sentiment analysis is performed, and in this process, a detailed analysis algorithm for detailed analysis of sentiment may be added.

Online reviews are created in the form of multimedia such as text, images, and videos, and feature selection using machine learning can also be used to select important words within the text. FS can filter out unnecessary words and improve classification performance in selecting important words. Alternatively, for an effective opinion mining model for sentiment analysis, a combination of a learning classifier and an attribute selection method FS may be used. Here, FS may be CFS (Correlation based Feature Selection), IG (Information gain), etc., and the classifier used for classification is Logistic Regression, Decision Tree, Neural Network, Support Vector. Machine (Support Vector Machine), Naive Bayesian Network, Random Forest, Bagging, Stacking, Random Subspace Any one or a combination of at least one can

FS, which appeared with the advent of data sets containing hundreds of thousands of attributes, can model the process of data creation and management and secure variables. to maintain or improve performance. For attribute selection, filter learning, in which the derivation algorithm learns as an independent preprocessing step, depends on the general properties of the data, and uses the algorithm as a black box, and predicts the relative usefulness of a subset of variables using predictive performance. Wrapper learning using a learning method as a subroutine that evaluates and calls a property selection algorithm to evaluate a subset of each feature (features) Subsets are displayed as included in the classification criteria construct, and can include embeddings that allow searching and finding dependencies in the combined space of subsets of properties and hypotheses.

IG is one of the single-variable methods of evaluation attributes. This method evaluates a function according to information acquisition and considers only one function at a time, and the entropy measurement is as shown in Equation 1 below.

Here, p(y) is the limiting probability density function for the random variable (Y). If the observed Y value in the training data set S is partitioned according to the second attribute, the X value, if the entropy of Y for the partition induced by X is smaller than the entropy of Y before the division, then the There is a relationship between the features. At this time, after observing X, Y is the same as in Equation 2 below.

where p(y|x) is the conditional probability of a given x. Given the entropy relative to the impurity in the training set S, we can define a measure that reflects the additional information about Y provided by X representing the amount by which the entropy of Y decreases. This measurement is an index indicating the dependency between X and Y, and is referred to as IG, and the resulting equation is as follows. In this case, a threshold value for providing regular classification of all attributes and selecting the number of attributes according to the obtained order may be preset.

CFS is a multivariate filter algorithm that ranks a subset of attributes according to a correlation-based heuristic evaluation function. This is a method of evaluating the error of whether or not subsets of included properties are correlated with each other. Heuristic evaluation deals with low-relevance variables that impede the performance of classification on target variables. Attributes with low relevance are excluded because they have low correlation with classes. Attribute selection can be performed independently.

Logistic regression is a regression analysis method used for the purpose of linear or non-linear classification. In this method, the output of the training instance belonging to each class is set to 1, and the output of the non-member instance is set to 0, and regression is performed on the class. A linear equation is derived from this result, and then, when performing unknown class verification, it is a classifier that calculates the result of each linear equation and classifies it by selecting the largest value. The goal of naive Bayesian is to accurately predict the class of a test instance by learning a training instance that includes class information. In this case, the Bayesian network can be specialized in the form of a naive because the naive Bayesian depends on two important simplification assumptions. In particular, it is assumed that the prediction properties are conditionally independent for each given class, and the identified or latent properties influence the prediction process.

The neural network is an algorithm that mimics the neurons of the human brain. It is a multilayer perceptron and consists of an input layer, a hidden layer, and an output layer. It is composed of nodes. Next, the hidden layer processes the variable values transmitted from the input layer as non-linear functions and transmits them to the output layer. The output layer has a node corresponding to the target variable. Random forest is an ensemble learning method for performing regression and other tasks, in which a large number of decision trees are constructed during a training period, and can be operated by classification mode or class output, which is the average prediction of individual trees.

Random forest is suitable for emotion classification because it is a more suitable classifier for sentiment classification compared to various ensemble classifiers due to the many overlapping values of text classification. In a random space, the training data set can be modified using algorithms such as bagging, where the modification can be done in attribute space rather than instance space. Random forest can use arbitrary subspaces to construct and aggregate base classifiers, and if the data set has a large number of redundant or unrelated properties, the base classifier is more effective in random subspaces compared to the original feature space. You can choose a classifier. The combined decision of this base classifier may outperform a single classifier built from the training dataset of the entire set of attributes.

A decision tree is a non-parametric method that can be applied to classification or regression tasks. It is a hierarchical data structure for supervised learning in which the input space is divided into local regions to predict the dependent variable. The support vector machine provides an optimal separation hyperplane state for solving the classification task. Mathematical analysis can represent nonlinear problems related to the input space as linear problems in high-dimensional isolated hyperplanes.

Bagging is an abbreviation of Bootstrap aggregating. After repeatedly sampling according to a uniform probability distribution, a decision tree model is combined to make classification prediction according to voting. Bagging is mainly used in regression analysis and can improve stability and accuracy and reduce variance. Unlike bagging, which combines models of the same type, stacking is the task of learning different learning algorithms to combine predictions from different algorithms. In particular, it is possible to find and combine the classifier with the best performance after estimating the performance of which classifier is reliable using the meta-learning machine.

The display unit 360 may overlay and display the translated text and the original text translated by the translator terminal 400 on the corrected text corrected by the correction terminal 500 . If the translated part and the original text are not displayed separately, the subscriber or user cannot determine which part of the translation is wrong or whether the correction is wrong. Therefore, the convenience is reduced. Accordingly, the original text, translation, and revision can be displayed when the mouse is over or touched in units of each word, phrase, or verse, so that you can intuitively know which part was modified and how the original text was modified in the native language. let it be In addition, it may be configured so that the user can modify it when he/she wants it, and may induce the participation of the general public even if he is not an expert.

The creation unit 370 counts the number of recommendations and the number of non-recommendations for the story content translated or corrected in the translator terminal 400 or the correction terminal 500, and based on the counted number of recommendations and non-recommendations to the creator terminal 100 It can be managed by assigning a grade. In this case, since the grade is a quantitative element, and the qualitative analysis corresponds to the opinion mining described above, a redundant description thereof will be omitted.

The distribution unit 380, when the story content is produced or published in any one of movies, dramas, animations, fairy tales and novels, or derivative works are derived from character business, toys and games, produced, published, derived works or 2 A preset percentage of the copyright fee and revenue for the derivative work may be distributed to the creator terminal 100 , the translator terminal 400 , and the correction terminal 500 . In addition, here, the copyright is a reproduction right, a performance right, a broadcasting right, a transmission right, an exhibition right, a distribution right, and a derivative work that is a creation created by translation, arrangement, transformation, adaptation, video production, or other methods of the original work. It is not limited to things In addition, works include novels, poems, thesis, lectures, speeches, screenplays and other literary works, musical works, plays, dances, pantomimes and other theatrical works, paintings, calligraphy, sculptures, prints, crafts, applied art works, and other fine arts. It may include works, models and design drawings for buildings and other architectural works, photographic works, visual works, maps, diagrams, plans, schematics, models and other graphic works, and computer program works, but is not limited to those listed does not

Hereinafter, an operation process according to the configuration of the content platform service providing server of FIG. 2 will be described in detail with reference to FIGS. 3 and 4 as an example. However, it will be apparent that the embodiment is only one of various embodiments of the present invention and is not limited thereto.

Referring to FIG. 3 , (a) when the content platform service providing server 300 receives story content from the creator terminal 100 , the web page, app page, and application provided by the content platform service providing server 300 . Or upload it to the program, and (b) receive a review or rating such as recommendation or non-recommendation from at least one user terminal (not shown). In addition, when the translator terminal 400 translates the story content and selects a different language but a page of another country or another page in the same platform or the same page, a recommendation or non-recommendation is received from the user terminal of the corresponding country. In this case, the content itself, that is, the recommendation and non-recommendation of the story content itself, and the recommendation and non-recommendation of the translation are separately provided so that it is possible to distinguish whether the story itself is bad or the translation is bad.

In addition, when corrections to the translation or machine translation are made, as described above, (c) receive reviews or ratings such as recommendations and dis-recommendations for the correction itself, and the rating or level of the modifier is determined by the received reviews or ratings. to give Giving a rating or level can be applied to translators and creators as well. In addition, when advertising revenue is generated, the content platform service providing server 300 distributes the revenue according to each contribution to the creator terminal 100 , the translator terminal 400 and the correction terminal 500 , and the secondary work is If it is derived, the profits can also be distributed. Referring to FIG. 4A , a platform structure in which a translation program and a real-time translation program can be used, and a creator, a translator, and a revised translator can receive revenue distribution according to their respective contributions is shown. In addition, FIG. 4b shows a profit structure for what kind of profit will be distributed to whom. However, the distribution of advertising revenue or product revenue is only a subject of agreement between the contracting parties, so it is not limited to the above-mentioned profit distribution structure. In addition, it is not limited to the above-described structure, and various structures and step-by-step flows may be possible.

As described above, the method of providing a story content platform service for distributing revenue to creators and multiple participants of FIGS. 2 to 4 is a method of providing a story content platform service for distributing revenue to creators and multiple participants through FIG. 1 above. Since it is the same as the content described with respect to or can be easily inferred from the described content, the following description will be omitted.

5 is a diagram illustrating a process in which data is transmitted/received between components included in the story content platform service providing system for distributing revenue to the creator and multiple participants of FIG. 1 according to an embodiment of the present invention. Hereinafter, an example of a process in which data is transmitted and received between each component will be described with reference to FIG. 5, but the present application is not limited to such an embodiment, and the example shown in FIG. 5 according to the various embodiments described above will be described. It is apparent to those skilled in the art that the data transmission/reception process may be changed.

Referring to FIG. 5 , the content platform service providing server maps the story content received from the creator terminal and the creator terminal into a database (S5100), and translates the story content into the language of each country using a pre-stored real-time translation program. and distribute (S5200).

The content platform service providing server maps and stores the translator terminal and the translated text when the translator terminal translates the story content translated by the artificial intelligence translation unit or the story content of the storage unit (S5300), and in the artificial intelligence translation unit in the correction terminal When the translated story content or the translated text is corrected, revenue distribution is performed in proportion to the corrected ratio (S5400).

The order between the above-described steps (S5100 to S5400) is only an example and is not limited thereto. That is, the order between the above-described steps S5100 to S5400 may be mutually changed, and some of these steps may be simultaneously executed or deleted.

As described above, the method of providing a story content platform service for distributing revenue to the creator and multiple participants of FIG. 5 is not described above, through FIGS. 1 to 4, a method of providing a story content platform service that distributes revenue to creators and multiple participants Since it is the same as the content described with respect to or can be easily inferred from the described content, the following description will be omitted.

The story content platform service providing method for distributing revenue to creators and multiple participants according to an embodiment described through FIG. 5 is a recording medium including instructions executable by a computer, such as an application or program module executed by a computer. It can also be implemented in the form of Computer-readable media can be any available media that can be accessed by a computer and includes both volatile and nonvolatile media, removable and non-removable media. Also, computer-readable media may include all computer storage media. Computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data.

The method for providing a story content platform service for distributing revenue to creators and multiple participants according to an embodiment of the present invention described above includes an application basically installed in a terminal (which includes a program included in a platform or operating system basically installed in the terminal) may be executed), and may be executed by an application (ie, a program) installed directly on the master terminal by a user through an application providing server such as an application store server, an application, or a web server related to the corresponding service. In this sense, the story content platform service providing method for distributing revenue to creators and multiple participants according to an embodiment of the present invention described above is implemented as an application (that is, a program) installed by default in a terminal or directly installed by a user It may be recorded in a computer-readable recording medium such as a terminal.

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

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

Claims (7)

A creator terminal that provides story content, and receives a distribution of revenue for copyright fees and secondary works of the provided story content;
a translator terminal that translates the text included in the story content and receives advertising revenue generated while the translated story content is consumed;
a correction terminal that corrects some or all of the text translated by the translator terminal, and receives the advertisement revenue distributed in proportion to the corrected ratio; and
A storage unit for mapping the story content received from the creator terminal and the creator terminal into a database; When the translator terminal translates the story content translated by the translation unit or the story content of the storage unit, a management unit that maps and stores the translator terminal and the translated text, the story content translated by the artificial intelligence translation unit in the correction terminal, or the When the translated text is corrected, a content platform service providing server including a distribution unit that distributes revenue in proportion to the corrected ratio;
A story content platform service providing system that distributes revenue to creators and multiple participants, including
The method of claim 1,
The content platform service providing server,
Count the number of recommendations and non-recommendations for the translation or correction of the story content translated or modified in the translator terminal or the correction terminal, and give a rating to the translator terminal or the correction terminal based on the counted number of recommendations and dislikes, and grant A rating unit that executes revenue distribution based on the graded rating;
Story content platform service providing system for distributing revenue to creators and multiple participants, characterized in that it further comprises.
3. The method of claim 2,
The content platform service providing server,
a display unit for overlaying and displaying the translated text and the original text translated by the translator terminal on the corrected text corrected by the correction terminal;
Story content platform service providing system for distributing revenue to creators and multiple participants, characterized in that it further comprises.
The method of claim 1,
The content platform service providing server,
a creation unit for counting the number of recommendations and non-recommendations for the story content translated or modified by the translator terminal or the revision terminal, and assigning a rating to the creator terminal based on the counted number of recommendations and disapproval;
Story content platform service providing system for distributing revenue to creators and multiple participants, characterized in that it further comprises.
The method of claim 1,
The content platform service providing server,
If the story content is produced or published in any one of movies, dramas, animations, fairy tales and novels, or derivative works are derived from character business, toys and games, copyright fees for the production, publication, derivative works or derivative works And a distribution unit for distributing a preset percentage of the revenue to the creator terminal, the translator terminal and the correction terminal;
Story content platform service providing system for distributing revenue to creators and multiple participants, characterized in that it further comprises.
The method of claim 1,
The artificial intelligence translation unit,
Story content that distributes revenue to creators and multiple participants, characterized in that it is translated in real time using a Neural Machine Translation model using a neural network or a pre-stored Corpus-based Statistical Machine Translation model Platform service provision system.
7. The method of claim 6,
The artificial intelligence translation unit,
When using the machine translation model using the neural network, a multi-lingual corpus is used in the learning process, and a first language is translated into a second language in a spoken language translation domain. and a story content platform service providing system that distributes revenue to multiple participants.

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