• Title of article

    Learning to construct knowledge bases from the World Wide Web

  • Author/Authors

    Mitchell، Tom نويسنده , , CRAVEN، MARK نويسنده , , DiPasquo، Dan نويسنده , , Freitag، Dayne نويسنده , , McCallum، Andrew نويسنده , , Nigam، Kamal نويسنده , , Slattery، Se?n نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2000
  • Pages
    -68
  • From page
    69
  • To page
    0
  • Abstract
    Morphology is the area of linguistics concerned with the internal structure of words. Information retrieval has generally not paid much attention to word structure, other than to account for some of the variability in word forms via the use of stemmers. We report on our experiments to determine the importance of morphology, and the effect that it has on performance. We found that grouping morphological variants makes a significant improvement in retrieval performance. Improvements are seen by grouping inflectional as well as derivational variants. We also found that performance was enhanced by recognizing lexical phrases. We describe the interaction between morphology and lexical ambiguity, and how resolving that ambiguity will lead to further improvements in performance.
  • Keywords
    Machine learning , Knowledge bases , Text classification , Relational learning , Web spider , Information extraction , world wide web
  • Journal title
    ARTIFICIAL INTELLIGENCE (NON MEMBERS) (AI)
  • Serial Year
    2000
  • Journal title
    ARTIFICIAL INTELLIGENCE (NON MEMBERS) (AI)
  • Record number

    47991