• DocumentCode
    2728179
  • Title

    Measuring Semantic Similarity between Named Entities by Searching the Web Directory

  • Author

    Liu, Jiahui ; Birnbaum, Larry

  • fYear
    2007
  • fDate
    2-5 Nov. 2007
  • Firstpage
    461
  • Lastpage
    465
  • Abstract
    The importance of named entities in information retrieval and knowledge management has recently brought interest in characterizing semantic relationships between entities. In this paper, we propose a method for measuring semantic similarity, an important type of semantic relationship, between entities. The method is based on Google Directory, a search interface to the Open Directory Project. Via the search engine, we can locate the web pages relevant to an entity and automatically create a profile of the entity according to the directory assignments of its web pages, which capture various features of the entity. Using their profiles, the semantic similarity between entities can be measured in different dimensions. We apply the semantic similarity measurement to two knowledge acquisition tasks: thesaurus construction of entities and fine grained categorization of entities. Our experiments demonstrate that the proposed method works effectively in these two tasks.
  • Keywords
    Humans; Information retrieval; Knowledge acquisition; Knowledge engineering; Knowledge management; Particle measurements; Search engines; Thesauri; USA Councils; Web pages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence, IEEE/WIC/ACM International Conference on
  • Conference_Location
    Fremont, CA
  • Print_ISBN
    978-0-7695-3026-0
  • Type

    conf

  • DOI
    10.1109/WI.2007.70
  • Filename
    4427135