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
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