Collective intelligence-based web page search: Combining folksonomy and link-based ranking strategy

Tao Zhang*, Byungjeong Lee, Sooyong Kang, Hanjoon Kim, Jinseog Kim

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

4 Citations (Scopus)

Abstract

With the exponentially growing amount of information available on the Internet, retrieving web pages of interest has become increasingly difficult. While several web page recommender systems have been developed, it is still difficult to search related information which reflects users' preference. In this paper, we propose a new type of web page search which is based on the collective intelligence. It combines folksonomy and link-based ranking evaluation scheme so as to accommodate users' preferences. We implemented the prototype system and demonstrate the feasibility of the proposed web page search scheme.

Original languageEnglish
Title of host publicationProceedings - IEEE 9th International Conference on Computer and Information Technology, CIT 2009
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages166-171
Number of pages6
Volume2
ISBN (Print)9780769538365
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventIEEE 9th International Conference on Computer and Information Technology, CIT 2009 - Xiamen, China
Duration: 11 Oct 200914 Oct 2009

Other

OtherIEEE 9th International Conference on Computer and Information Technology, CIT 2009
CountryChina
CityXiamen
Period11/10/0914/10/09

Keywords

  • Collective intelligence
  • Folksonomy
  • Link-based web search
  • Ranking strategy

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