• DocumentCode
    2457494
  • Title

    Incorporating users location into snippet based Query recommendation system

  • Author

    Sisode, Megha R. ; Patil, Ujwala M.

  • Author_Institution
    Dept. of Comput. Eng., R.C. Patel Inst. of Technol., Shirpur, India
  • fYear
    2015
  • fDate
    8-10 Jan. 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    As the access of web has been increased greatly for information retrieval and it is difficult to extract the relevant information in less time. Sometime Search engine does not able to understand user search intend behind query. Thus Query recommendation can be used to help user to state exactly their information need. Search engine can return appropriate result to meet users´ information needs. There are various methods based on history of users and snippets to retrieve the information. But these methods fail to satisfy users need. Therefore in addition of history and snippets with users location information will produce better results. Snippet based method with incorporating users preferences and location results the URLs for given query, also it ranks the clicked URLs at the top of the result based on user profile. The performance of the system shows that the snippet based with incorporating users location give better and effective recommendation for all types queries as compared to previous methods including low frequency queries.
  • Keywords
    Internet; information needs; query processing; recommender systems; search engines; URL; Web access; information retrieval; search engine; snippet-based query recommendation system; user location; user profile; Androids; Data mining; Databases; Google; Humanoid robots; Search engines; information retrieval; query recommendation; snippets; user profile; users location;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pervasive Computing (ICPC), 2015 International Conference on
  • Conference_Location
    Pune
  • Type

    conf

  • DOI
    10.1109/PERVASIVE.2015.7087079
  • Filename
    7087079