Computing temporal trends in web documents

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

1 Scopus citations

Abstract

Most existing methods of web content mining assume a static nature of the web documents. This approach is inadequate for long-term monitoring and analysis of the web content, since both the users' interests and the content of most web sites are subject to continuous changes over time. In this research, we are interested in developing computationally intelligent and efficient text mining techniques that will enable continuous comparison between documents provided by the same source (website, institute, organization, cult, author etc.) or viewed by the same group of users (e.g., university students) and timely detection of temporal trends in those documents. Our approach builds upon the recently developed methodology for fuzzy comparison of frequency distributions. The proposed techniques are evaluated on a real-world stream of web traffic.

Original languageEnglish
Title of host publicationProceedings - 4th Conference of the European Society for Fuzzy Logic and Technology and 11th French Days on Fuzzy Logic and Applications, EUSFLAT-LFA 2005 Joint Conference
Pages615-620
Number of pages6
StatePublished - 1 Dec 2005
EventJoint 4th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2005 and 11th French Days on Fuzzy Logic and Applications, LFA 2005 - Barcelona, Spain
Duration: 7 Sep 20059 Sep 2005

Publication series

NameProceedings - 4th Conference of the European Society for Fuzzy Logic and Technology and 11th French Days on Fuzzy Logic and Applications, EUSFLAT-LFA 2005 Joint Conference

Conference

ConferenceJoint 4th Conference of the European Society for Fuzzy Logic and Technology, EUSFLAT 2005 and 11th French Days on Fuzzy Logic and Applications, LFA 2005
Country/TerritorySpain
CityBarcelona
Period7/09/059/09/05

Keywords

  • Automated Perceptions
  • Text Mining Trend Detection
  • Trend Discovery
  • Web Content Mining

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Information Systems

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