TWM649741U - Similar internet celebrity matching recommendation system - Google Patents

Abstract

This invention discloses a similar internet celebrity matching recommendation system, including a data exploration device, a data storage, a data processor and a computer device. The data mining device connects to the social platform through the Internet, and searches and retrieves Internet celebrity information in the social platform based on the target characteristics of the target Internet celebrity; the Internet celebrity information has similar characteristics, and the similar characteristics are similar to the target characteristics. The data storage device is connected to the data exploration device and stores multiple Internet celebrity data. The data processor connects to the data storage and uses algorithms to analyze and compare the similarity between the target features and similar features to generate initial internet celebrity ranking data. The computer device is connected to the data processor and weights the initial influencer ranking data according to the weighted ratio to generate similar influencer analysis results of similar target influencers.

Description

Similar internet celebrity matching recommendation system

This creation is about an Internet celebrity analysis and recommendation system, especially a similar Internet celebrity matching recommendation system.

Nowadays, the speed of Internet communication is fast and there are many social media. As a result, many Internet celebrities (hereinafter referred to as Internet celebrities) have emerged to perform through various social media to attract fans to watch. For fans, there are a large number of Internet celebrities today with different styles and characteristics. Therefore, if similar Internet celebrities can be recommended to fans, it can further promote the interaction between Internet celebrities and fans.

In the existing technology, the recommendation method of similar Internet celebrities mainly relies on the interaction generated by fans on Internet celebrity social media, such as likes, comments, shares and other interactive data. After further analyzing the fans' preferences, similar Internet celebrities are Recommended to fans. However, because the existing technology often ignores important similarity indicators, such as the content style and audience composition of Internet celebrities, it is impossible to comprehensively assess the similarity between Internet celebrities.

In addition, the existing technology is also easily affected by data sparsity, data validity and data integrity in the analysis of similar Internet celebrities, resulting in distortion of the analysis results, making it impossible to accurately and ideally recommend similar Internet celebrities to fans.

Accordingly, how to provide a matching recommendation system for similar internet celebrities has become an urgent research topic.

This invention discloses a similar internet celebrity matching recommendation system, which includes a data exploration device, a data storage, a data processor and a computer device. The data mining device connects to at least one social platform through a network, and searches and retrieves data on a plurality of Internet celebrities in at least one social platform based on at least one target characteristic of a target Internet celebrity; wherein the data on the plurality of Internet celebrities has At least one similar feature is similar to at least one target feature. The data storage device is connected to the data exploration device and stores multiple Internet celebrity data. The data processor is connected to the data storage and uses at least one algorithm to analyze and compare the similarity between at least one target feature and at least one similar feature to generate initial internet celebrity ranking data. The computer device is connected to the data processor and weights the initial influencer ranking data according to a weighted ratio to generate similar influencer analysis results of similar target influencers.

Following the above, this creation provides a similar internet celebrity matching recommendation system based on multi-dimensional characteristics, which evaluates the similarity between the target internet celebrity and similar internet celebrities from multiple aspects, allowing fans to more conveniently and quickly find those with similar characteristics. Internet celebrities, Internet celebrities and advertisers can also carry out precise promotion and cooperation based on the recommendation results.

Please refer to Figure 1, which is a block diagram of the similar internet celebrity matching recommendation system of this creation. The similar internet celebrity matching recommendation system 1 includes a data exploration device 11 , a data storage 12 , a data processor 13 and a computer device 14 . The data mining device 11 connects to at least one social platform F through a network, and searches and retrieves plural Internet celebrity data in at least one social platform F based on at least one target characteristic of a target Internet celebrity. The plurality of Internet celebrity materials have at least one similar feature, and at least one similar feature is similar to at least one target feature. The data storage 12 is connected to the data exploration device 11 and stores a plurality of internet celebrity data. The data processor 13 is connected to the data storage 12 and uses at least one algorithm to analyze and compare the similarity between at least one target feature and at least one similar feature to generate initial internet celebrity ranking data. The computer device 14 is connected to the data processor 13 and weights the initial influencer ranking data according to a weighted ratio to generate similar influencer analysis results of similar target influencers. By using this similar internet celebrity matching recommendation system 1, a system platform as shown in Figure 2 of this case can be provided for users to browse and refer to the ranking and analysis results of similar internet celebrities.

The target characteristics of the target Internet celebrity include an Internet celebrity style characteristic, a fan composition characteristic, and an interaction mode characteristic. Each characteristic can have a high or low weighting ratio set accordingly. In the embodiment of this creation, the influencer style characteristics and fan composition characteristics can be set to have a higher weighting ratio, and the interaction mode characteristics have a lower weighting ratio. In this creation, the high and low ratios are not limited. Therefore, the similar influencer matching recommendation system 1 performs similarity evaluation and analysis on influencers in various social media by setting the target characteristics of the target influencer. For example, the similar influencer matching recommendation system 1 searches for target influencers through keywords, and selects one of the target influencers through tags, gender, filters, etc., and generates recommended target influencers for subsequent similarity. Internet celebrity analysis.

Internet celebrity style features include a post style feature, a comment style feature, and a picture image style feature. Post style characteristics include - games, - beauty and fashion, - health, - food, - arts and entertainment, - sports, - business and economics, - family and relationships, - technology, - law, politics and society, - travel, - Education, work and study, one pet, one life, one religious numerology, one adult, one transportation, one daily topic and one climate and environment post style feature, the comment style feature includes an industry and economic style feature, and a political news style feature , an entertainment media style feature, the header image style feature includes a gender style feature, a dress style feature and a modeling style feature. For example, if the Internet celebrity often posts photos of tourist attractions and introductions to food stores on social media, the data processor 13 can analyze and summarize the images and text captured by the algorithm to determine whether the Internet celebrity belongs to Internet celebrities with travel style characteristics. Furthermore, the profile image of the internet celebrity captured through the data mining device 11 is a female image feature, and the data processor 13 uses an algorithm to identify that the hair style and dress style features of the internet celebrity are similar to Based on the style characteristics of Korean artists, the data processor 13 can analyze and conclude that the Internet celebrity belongs to Korean-style Internet celebrities. Similarly, the style characteristics of other Internet celebrities can be deduced in the same way and will not be described again here.

Fan composition characteristics include gender characteristics, number characteristics, regional characteristics, national characteristics and age characteristics. By searching, retrieving and comparing similar fan composition characteristics, users can be provided with relatively similar internet celebrity styles. Gender characteristics and age characteristics can be collected through algorithms to identify the gender and age range of fans. Population characteristics can be known through the number of fans of the target Internet celebrity. Regional characteristics and country characteristics can be collected through algorithms to classify the fans' check-in locations into groups. For example, through the data mining device 11, it is captured that most of the fans of the target Internet celebrity are male, the number is about 1 million, the age range is between 20 and 30 years old, the country and region is Taipei City, Taiwan, and the data processing Tool 13 can analyze and conclude that the target internet celebrity is a Taiwanese female internet celebrity, and her age is also between 20 and 30 years old.

The characteristics of the interaction mode include the frequency of replying to the Internet celebrity's messages, the frequency of sharing the Internet celebrity's messages, the Internet celebrity's like rate, and the Internet celebrity's posting rate. Records of various interaction modes are searched and retrieved through the data mining device 11 and compared by the data processor 13 Similar interaction mode features can provide users with relatively similar Internet celebrity styles. For example, when the user's like rate for the target internet celebrity reaches 70%, and when the like rate of another internet celebrity reaches 65% through the data mining device 11, the data processor 13 can search and retrieve the like rate of the target internet celebrity. Internet celebrities with similar like ratios are classified as similar Internet celebrities. Similarly, the frequency of replying to Internet celebrities' messages, the frequency of sharing of Internet celebrities' messages, and the ratio of Internet celebrities' postings can be deduced and will not be repeated here.

In this creation, the similar internet celebrity matching recommendation system 1 uses various algorithms to automatically capture, analyze and convert similar characteristics of similar internet celebrities, and uses various algorithms and weighting ratios to recommend similar internet celebrities for users. In this creation, algorithms include deep learning algorithms, natural language algorithms, image recognition algorithms, and crawler algorithms.

The natural language algorithm and the crawler algorithm compare the degree of similarity between at least one target feature and at least one similar feature based on the plurality of Internet celebrity information and keyword analysis in the target Internet celebrity's messages, comments, or posts. In this creation, the data processor 13 uses a crawler algorithm combined with a natural language algorithm to analyze the similarity of the semantic content of the Internet celebrity's posts, and when the semantic analysis content is similar, the Internet celebrity posts similar Internet celebrities. Tags to classify content. For example, when the target Internet celebrity often posts articles about Taipei food on social media, and it is retrieved through the crawler algorithm that another Internet celebrity often posts articles about Taipei food on social media, even When the Internet celebrity and the target Internet celebrity mention each other's names, the data processor 13 can use the natural language algorithm to infer from the semantics that the Internet celebrity and the target Internet celebrity are related or have intersections. , therefore, classify this internet celebrity as a similar internet celebrity.

The image recognition algorithm analyzes and compares the degree of similarity between at least one similar feature and at least one target feature based on the internet celebrity images of the plurality of internet celebrity data and the target image of the target internet celebrity. For example, the image recognition algorithm identifies the characteristics of the Internet celebrity's hair style in the Internet celebrity image, and the target image of the target Internet celebrity also has the characteristics of the Internet celebrity's hair style. The data processor 13 can use the image recognition algorithm to identify the characteristics of the Internet celebrity's hair style. This influencer is classified as a similar target influencer. Alternatively, when the target Internet celebrity and the Internet celebrity have tagged (Hashtag) the same person or tagged the same group of people on social media, the data processor 13 can use the image recognition algorithm to identify the target Internet celebrity through the image recognition algorithm. The influencers are classified as similar target influencers.

The deep learning algorithm analyzes and compares the degree of similarity between at least one target feature and at least one similar feature based on the frequency of replying to the internet celebrity's messages, the frequency of sharing the internet celebrity's messages, and the rate of the internet celebrity's likes. For example, the above-mentioned internet celebrity like ratio can be compared for similarity through a deep learning algorithm, and the degree of similarity of the internet celebrity can be judged based on the learning ratio. Or, judge by analyzing the interactive performance characteristics of the Internet celebrity. For example, if the fan composition characteristics of the target Internet celebrity and similar Internet celebrities both have about 1 million fans, but the influence and interaction performance of the target Internet celebrity on social media are mainly targeted at fans of the travel group, while another The influence and comments of Internet celebrities on social media are analyzed through natural language processing. It is found that their comments are mainly targeted at fans of political groups. Therefore, the Internet celebrity can be judged by analyzing the interactive performance characteristics of the Internet celebrity. It is not similar to the target influencer.

In addition, this creation can use the above-mentioned various algorithms to convert various similar features into a corresponding absolute value or relative value, so as to facilitate subsequent similarity evaluation based on the numerical value. In this creation, the absolute value is such as the number of likes of the Internet celebrity's post, and the relative value is such as the frequency of replying to the Internet celebrity's message. Furthermore, the degree of similarity can also be analyzed and judged based on the combination of various similar features, and is not limited to matching and comparison with a single similar feature alone.

The data processor 13 uses the above algorithm to analyze and compare the degree of similarity between the target feature and similar features, and generates initial internet celebrity ranking data to the computer device. The computer device 14 generates a weighted ratio based on an event message generated by a plurality of users. In this creation, event messages include multiple users' click messages on a similar influencer in the initial influencer ranking data, a favorite influencer message, a subscription influencer message, and a product transaction message. In this invention, the computer device 14 uses an artificial intelligence algorithm to generate a voting ratio based on event information such as similar Internet celebrity click messages, collection of Internet celebrity messages, subscription to Internet celebrity messages, or commodity transaction information, and learns based on the voting ratio. The analysis yields weighted proportions.

Please refer to Figure 2, which is a schematic diagram of the initial internet celebrity ranking data for this creation. In the initial Internet celebrity ranking data, with J Internet celebrity as the target Internet celebrity, a total of 5 Internet celebrities from A to E were analyzed and recommended to users. However, for users, everyone has different reasons for liking Internet celebrities. Therefore, the computer device 14 uses artificial intelligence technology to learn and analyze event messages generated by multiple users to adjust the generated weighting ratio. For example, if the data processor 13 generates a ranking list of recommended Internet celebrities, from left to right, the first one is Internet celebrity A, and the fifth one is Internet celebrity E, and when many users think that Internet celebrity B is their The candidate who is more like and similar to Internet celebrity J. Therefore, when the user clicks on the link of Internet celebrity B to view, through web tracking technology, for example, the value of the click message of the similar Internet celebrity can be tracked and counted, and sent to the similar Internet celebrity Matching recommendation system 1. Furthermore, when a user performs various actions such as clicking and collecting similar Internet celebrities on the web interface of the Similar Internet Celebrity Matching Recommendation System 1 platform of this creation, event messages (events) are generated, and the event is sent by the front end and back end of the website. The information is sent to the database of the Similar Internet Celebrity Matching and Recommendation System 1. The Similar Internet Celebrity Matching and Recommendation System 1 automatically reads, counts, tracks and optimizes these event messages through algorithms to track and calculate the value of similar Internet celebrity click messages. The event information is self-defined by the similar internet celebrity matching recommendation system 1 and includes various event information such as user information, behavior information, context information, user account information, source and login information. When the number of click messages from similar Internet celebrities is greater than the preset threshold, it means that Internet celebrity B is actually an Internet celebrity that many users love. Therefore, the artificial intelligence technology adjusts the weighting ratio to increase the score of Internet celebrity B, so that The ranking of B influencer can be improved upward, for example, to the previous position. Similarly, if many users collect Internet celebrity C as their favorite Internet celebrity list, collecting Internet celebrity information through statistics should be able to obtain a higher weighting ratio than clicking on the message. Artificial intelligence technology will adjust the ranking list of Internet celebrities. . Similarly, if a user engages in product trading behavior and generates product trading information through the product introduction of D influencer, D influencer should be able to obtain the highest weighted ratio on the influencer ranking list. Therefore, artificial intelligence technology will Adjust the ranking list of D influencers. The corresponding relationship between the weighted proportion and the event messages generated by other users can be deduced by analogy and will not be described in detail here.

In addition, in the embodiment of the present invention, the computer device 14 can generate different voting proportions based on various event messages, and generate a weighted proportion based on voting proportion learning analysis. Taking the above collection of Internet celebrity information as an example, when many users click on Internet celebrity B on the similar Internet celebrity matching recommendation system 1, as a list of favorite Internet celebrities, artificial intelligence technology can learn based on this to generate a weighted proportion of 0.4. When many users collect Internet celebrity C as their favorite Internet celebrity list, artificial intelligence technology can learn to generate a weighted proportion of 0.6 based on this. When many users purchase related products through the product introduction of D influencer, the artificial intelligence technology can learn to generate a weighted ratio of 0.9. Compared with the above situation of setting a preset quantity threshold and judging whether the values of various event messages are greater than the preset quantity threshold, artificial intelligence technology can be used to more flexibly learn to generate weighted proportions in response to various situations.

In addition, in order to prevent the same user from repeatedly clicking on the same influencer within a short period of time, resulting in an increase in the number of similar influencer click messages, the above-mentioned web tracking technology can be used to track and analyze the user's account, source, login method and other information to eliminate Repeated click behavior.

Please refer to Figure 3, which is a block diagram of the similar internet celebrity matching recommendation system including a data storage device and a data search device. The data storage device 15 is connected to the computer device 14, and uses a data storage technology to establish an Internet celebrity data index (index) corresponding to the target Internet celebrity and a plurality of similar Internet celebrities according to the similar Internet celebrity analysis results. The data search device 16 is connected to the data storage 12 and searches for the target Internet celebrity and a plurality of similar Internet celebrities according to the index index. The data search device 16 can use search engine technology to search for the target Internet celebrity and a plurality of similar Internet celebrities, and output the similar Internet celebrity analysis results through the subsequent data display 17 . For example, according to the analysis results of similar influencers, the target characteristics of a certain target influencer are women aged between 30 and 40 in the United States. When searching through index indicators, the relationship between the target characteristics and similar characteristics can be more quickly identified. Search recommended Internet celebrities to further improve search efficiency and recommend them to favorite users.

Please refer to Figure 4. Figure 4 is a schematic block diagram of the similar internet celebrity matching recommendation system including a data display. The data display 17 is connected to the computer device 14 through an application programming interface (API), and outputs similar internet celebrity analysis results as shown in FIG. 4 . Users can receive similar influencer analysis results through a smart device, or connect to the product frontend of the similar influencer matching recommendation system 1 to receive similar influencer analysis results.

It should be noted that in this creative embodiment, each device and component in the similar internet celebrity matching recommendation system 1 actually corresponds to various hardware. For example, the data exploration device 11 is a hardware device of a data search engine. The data storage 12 is the hardware of a virtual server, a data register or a volatile memory, the data processor 13 is the hardware of a central processing unit or a cloud server, and the computer device 14 is A data computing and processing hardware, the data storage device 15 is a cloud server, a non-volatile memory or a hard disk hardware, the data search device 16 is a data processing device or a data search device , the data display 17 is a display hardware, which is not limited in this invention.

To sum up, this creation provides a similar internet celebrity matching recommendation system based on multi-dimensional features, which evaluates the similarity between the target internet celebrity and similar internet celebrities from many aspects, allowing users to more conveniently and quickly find those with similar characteristics. Internet celebrities, Internet celebrities and advertisers can also carry out precise promotion and cooperation based on the recommendation results and ranking, and send advertising messages to users on the same social platform. In addition, this creation uses algorithms such as deep learning, natural language processing, image recognition, and crawlers to automatically extract various features to generate analysis results, and uses machine learning algorithms to calculate and adjust weights based on text and images in the analysis results. scores to generate recommended similar internet celebrities, and to verify whether similar internet celebrities recommended by this creation match the internet celebrities recommended by this creation and the internet celebrities that the user is interested in, expects and likes through various event messages responded by the user, so as to improve the recommendation of this creation Accuracy of similar influencers.

In addition, in the similarity evaluation stage of this creation, the similar Internet celebrity matching recommendation system uses various algorithms to calculate the similarity indicators between Internet celebrities and ranks the Internet celebrities according to the indicators. In addition, the similar influencer matching recommendation system can also make personalized recommendations based on the user's preferences and historical behavior. Finally, in the recommendation stage, the similar Internet celebrity matching recommendation system will recommend a series of similar Internet celebrities to users based on similarity indicators and user preferences. Users can browse and follow similar Internet celebrities based on the recommendation results to better explore the Internet. Red ecology.

1: Similar internet celebrity matching recommendation system 11: Data exploration device 12:Data storage 13:Data processor 14:Computer device 15:Data storage device 16:Data search device 17:Data display F:Social platform

Figure 1 is a block diagram of the similar internet celebrity matching recommendation system created in this work; Figure 2 is a schematic diagram of the initial internet celebrity ranking data for this creation; Figure 3 is a block diagram of the similar internet celebrity matching recommendation system including a data storage device and a data search device; and Figure 4 is a schematic block diagram of the similar internet celebrity matching recommendation system including a data display.

1: Similar internet celebrity matching recommendation system

11: Data exploration device

12:Data storage

13:Data processor

14:Computer device

F:Social platform

Claims (15)

A similar internet celebrity matching recommendation system, including: A data mining device is connected to at least one social platform through a network, and searches and retrieves plural Internet celebrity information in the at least one social platform based on at least one target characteristic of a target Internet celebrity; wherein the plurality of Internet celebrity information is The Internet celebrity information has at least one similar characteristic, and the at least one similar characteristic is similar to the at least one target characteristic; A data storage device connected to the data mining device to store the plurality of internet celebrity data; A data processor, connected to the data storage, uses at least one algorithm to analyze and compare a degree of similarity between the at least one target feature and the at least one similar feature to generate an initial internet celebrity ranking data; and A computer device is connected to the data processor and weights the initial Internet celebrity ranking data according to a weighted ratio to generate a similar Internet celebrity analysis result that is similar to the target Internet celebrity. The similar internet celebrity matching recommendation system as described in claim 1, wherein the target feature includes an internet celebrity style feature, a fan composition feature and an interaction mode feature. Similar Internet celebrity matching recommendation system as described in request item 2, wherein the Internet celebrity style feature includes a post style feature, a comment style feature, and a picture image style feature; wherein the post style feature includes a game, a Beauty and fashion, one health, one food, one art and entertainment, one sports, one business and economy, one family and relationship, one technology, one law, politics and society, one travel, one education, work and study, one pet, one Life, a religious numerology, an adult, a vehicle, a daily topic and a climate and environment style feature, the profile picture style feature includes a gender style feature, a dress style feature and a modeling style feature. The similar internet celebrity matching recommendation system as described in claim 2, wherein the fan composition characteristics include a gender characteristic, a number characteristic, a regional characteristic, a country characteristic and an age characteristic. A similar internet celebrity matching recommendation system as described in request item 2, wherein the interaction mode characteristics include a frequency of replying to messages from an internet celebrity, a frequency of sharing messages from an internet celebrity, a rate of likes from an internet celebrity, and a rate of posts from an internet celebrity. The similar internet celebrity matching recommendation system as described in claim 1, wherein the algorithm includes a deep learning algorithm, a natural language algorithm, an image recognition algorithm, and a crawler algorithm. The similar internet celebrity matching recommendation system as described in claim 6, wherein the deep learning algorithm, the natural language algorithm and the crawler algorithm are based on the plurality of internet celebrity information and a message, a comment or a comment of the target internet celebrity. A keyword analysis in a post compares the degree of similarity between the at least one target feature and the at least one similar feature. The similar Internet celebrity matching recommendation system as described in claim 6, wherein the image recognition algorithm is based on an Internet celebrity image of the plurality of Internet celebrity data and a target image of the target Internet celebrity to analyze and compare the at least one similar Internet celebrity The degree of approximation of the feature to the at least one target feature. The similar internet celebrity matching recommendation system as described in request item 6, wherein the deep learning algorithm analyzes and compares the at least one target based on the internet celebrity's message reply frequency, the internet celebrity's message sharing frequency and the internet celebrity's like rate. The degree of similarity of a feature to the at least one similar feature. The similar internet celebrity matching recommendation system as described in claim 1, wherein the data processor analyzes the similarity degree of a semantic meaning for a post of the plurality of internet celebrity information through a crawler algorithm combined with a natural language algorithm, And when the semantic analysis content is similar, the plurality of Internet celebrity data is affixed with a label of a similar Internet celebrity. The similar internet celebrity matching recommendation system as described in claim 1, wherein the computer device generates the weighted ratio based on an event message generated by a plurality of fans. The similar internet celebrity matching and recommendation system as described in claim 11, wherein the computer device uses an artificial intelligence algorithm to determine whether a similar internet celebrity clicks on a message, a favorite internet celebrity, a subscription to an internet celebrity or a commodity transaction message. The majority generates a voting proportion, and learning and analysis based on the voting proportion generates the weighted proportion. The similar Internet celebrity matching recommendation system as described in claim 11 further includes a data storage device connected to the computer device, and uses a data storage technology to establish the plurality of Internet celebrity information corresponding to the target network based on the similar Internet celebrity analysis results. Red one index indicator. The similar influencer matching recommendation system described in claim 13 further includes a data search device connected to the data storage device to search the plurality of influencer information and the target influencer according to the index index. The similar influencer matching recommendation system as described in claim 14 further includes a data display connected to the computer device through an application program interface to output the similar influencer analysis result.

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