• DocumentCode
    1930486
  • Title

    Effect of Named Entities in Web Page Classification

  • Author

    Samarawickrama, Sameendra ; Jayaratne, Lakshman

  • Author_Institution
    Sch. of Comput., Univ. of Colombo, Colombo, Sri Lanka
  • fYear
    2012
  • fDate
    25-27 Sept. 2012
  • Firstpage
    38
  • Lastpage
    42
  • Abstract
    With the rapid multiplication of World Wide Web, there is an increasing requirement for automated web page classification techniques. Web page classification is an important task in web mining and is utilized in many other areas of research as well. General practice during classification is to use lexical terms as features. In this paper we investigate the effect of considering named entities as features in web page classification. We have conducted tests in five different domains â"-baseball, football, health, politics and science â"-with web pages collected from online news providers. Our results show that incorporating named entities can result in slight gains in classifier performance for narrow domains, but is not always true for all the domains. Results also showed that classification based only on named entities can be good for certain domains (e.g., baseball) but is still lower than the lexical terms based representation.
  • Keywords
    Web sites; classification; data mining; Web mining; World Wide Web; automated Web page classification; lexical terms; named entities; Accuracy; Dictionaries; Educational institutions; Feature extraction; Machine learning; Sports equipment; Web pages; named entities; web mining; web page classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence, Modelling and Simulation (CIMSiM), 2012 Fourth International Conference on
  • Conference_Location
    Kuantan
  • ISSN
    2166-8531
  • Print_ISBN
    978-1-4673-3113-5
  • Type

    conf

  • DOI
    10.1109/CIMSim.2012.55
  • Filename
    6338042