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Exploiting Social Data to Enhance Web Search

  • Vo Hoang PhucEmail author
  • Vu Thanh NguyenEmail author
  • Le Dinh Tuan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11814)

Abstract

With the strong growth of the internet, the search engine systems have been growing rapidly to allow web users to find relevant information with respect to their interests and needs. However, the amount of information is huge, searching information problems for users’ demands still remain many challenges. Many social platforms and networks (such as Twitter, Facebook or Delicious) which allow users to tag, share and organize their favorite web pages online using social annotations easily. Moreover, these social annotations could benefit web search because of user’s interesting tags and relevant information. Therefore, this paper proposed a search engine by combining following studies: (1) exploit social data from Twitter, (2) formulate query by personalized query expansion method using social annotations (SoQuES), (3) enhance the representation of documents and personalize them with social information (PerSaDoR), (4) use the social personalized ranking function (SoPRa) to re-rank search results. Furthermore, our experiment on Twitter data showed that our method could enhance the search engine user efficiently.

Keywords

Social annotation Personalized social ranking Query expansion Information search 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of Information TechnologyHo Chi Minh CityVietnam
  2. 2.Van Hien UniversityHo Chi Minh CityVietnam
  3. 3.Long An University of Economics and IndustryTân AnVietnam

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