Recommendations based on user profiles discovered from Facebook Like List

• Main Authors: Lee, Rong-Wei, 李榮維
• Other Authors: 劉敦仁、林君信
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/67581753205746612624

碩士 === 國立交通大學 === 管理科學系所 === 100 === After the fever of web 2.0 when blogging embarked on a new era of internet community, social networks have flourished in recent years and become another Internet golden era. Besides the traditional blog website, many new types of social network websites such as Facebook, MySpace or Microblog Twitter, Plurk came up. Social network websites have changed user behaviors on Internet nowadays dramatically. In facebook, personal interests or needs are disclosed when users post messages on the wall, reply friends’ messages, push “like” messages or join “fan pages”. This research proposes to recommend fan pages, friends and advertisements through discovering user interests from Facebook users’ “like list”. In this thesis, Formal Concept Analysis (FCA) is adopted to analyze the relation between fan pages in the like list. Afterwards, concepts that are appropriate to represent users’ interests are extracted to generate user profiles. Finally, a prototype System is developed to demonstrate the research result of recommending friends, fan pages and advertisements based on the discovered user profiles.