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• W52896586 abstract "The huge supply of information content in the Internet and its continuous growth makes the selection process more difficult for end users. Many filtering systems have been created to help users wade through the large amount of information, but they proved ineffective, not just because of the information overload, but also because of the type and quality of the information deemed relevant to users. This particular problem is being experienced by Facebook users. They see their Facebook page incessantly populated with irrelevant content, which significantly hinders reading what is indeed relevant for them. Facebook has made a first attempt at solving this problem by creating their own filtering system,which sorts the user stream based on some notion of relevance. However, their approach is not very effective since it often misses to identify the posts which are indeed the most relevant to users. Concerned with this problem, our research focused on developing a more effective filtering system, capable of finding the real user preferences. Recent studies point to the existence of an user profile that can be personal and selective, which becomes more efficient and responsive when it is built in a filtering system. So choosing the best features for a user profile is crucial on a filtering system. The result of our research is the Facebook Filter Plugin, a web-service that uses four different APIs that work together to build a content filtering system. It uses Facebook API, Google Prediction API, Google Cloud Storage and Google Chrome Extensions." @default.
• W52896586 created "2016-06-24" @default.
• W52896586 creator A5056512994 @default.
• W52896586 date "2012-07-28" @default.
• W52896586 modified "2023-09-26" @default.
• W52896586 title "Middleware for Facebook: Information Analysis and Filtering" @default.
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• W52896586 hasPublicationYear "2012" @default.
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