A Mobile Application Recommendation Method Integrating Social Network and Item Features
A mobile application and social network technology, applied in special data processing applications, instruments, electrical digital data processing, etc., to achieve the effect of improving accuracy and improving accuracy
Active Publication Date: 2017-09-29
CENT SOUTH UNIV
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However, recommendation systems that integrate social relationships generally focus on the social network itself, such as friend recommendation, social recommendation, etc. How to combine social relationship with mobile application recommendation according to the characteristics of mobile application recommendation still needs further research
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[0095] Since Douban.com contains both user rating information on mobile applications and interaction information between users, the present invention uses a web crawler to crawl relevant data information from Douban. The crawled data set contains 5462 rating information of 178 mobile applications by 298 users, and 19194 communication information between 4932 users. Wherein, the scoring information is an integer of 1-5. figure 1 This is an example of rating information for mobile applications, including scores and comments of several users on "Angry Birds 2". The number of stars in the figure is the user's rating, one star represents 1 point, two stars represent 2 points, and so on; the mobile application information includes the name and profile information of the mobile application, figure 2 An example of profile information for a mobile application. image 3 As an example of user exchange information, it shows the interaction information between the user "Big Era Diva" an...
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The present invention discloses a mobile application recommendation method with a social network and a project feature fused. The method comprises: firstly, calculating a similarity degree between mobile application projects by using a body-based semantic similarity degree method; then clustering the similar projects by a K-means method; and further improving a calculation method for a user similarity degree by using scores of a user on the similar projects, instead of calculating the user similarity degree by using scores of the user on the same projects in a traditional user-based collaborative filtering recommendation algorithm. In order to make full use of a user trust relationship in the social network, a project similar feature and the user trust relationship are fused into a scoring prediction formula, which effectively improves accuracy of prediction. As an experimental result shows, user similarity degree calculation based on K-means application project clustering and the user trust relationship are fused, which can improve accuracy of mobile application recommendation. The mobile application recommendation method disclosed by the present invention improves accuracy of mobile application recommendation, and has adaptivity to recommendation of other objects.
Description
technical field [0001] The field of mobile application recommendation involved in the present invention is, in particular, a mobile application recommendation method that integrates social network and item features. Background technique [0002] In recent years, the development of mobile applications is very rapid. However, the long-tail problem that has existed in the mobile application industry for a long time cannot be ignored. The common market share occupied by some applications with low demand and download volume can be equal to or even larger than that of mainstream applications. At the same time, there are problems in the mobile application market, such as few explicit feedbacks and low reliability of scoring data. Most domestic application market recommendations only consider the two factors of ratings and downloads, while the academic community focuses on application recommendations based on social relationships. However, there is still a lot of room for improveme...
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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 邝砾于美琪呙斌曹高峰
Owner CENT SOUTH UNIV