Title of article
The complexity of approximating MAPs for belief networks with bounded probabilities
Author/Authors
Abdelbar، Ashraf M. نويسنده , , Hedetniemi، Stephen T. نويسنده , , Hedetniemi، Sandra M. نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2000
Pages
-282
From page
283
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
Bipartite networks , Bayesian belief networks , Satisfiability , complexity , Local variance bound
Journal title
ARTIFICIAL INTELLIGENCE (NON MEMBERS) (AI)
Serial Year
2000
Journal title
ARTIFICIAL INTELLIGENCE (NON MEMBERS) (AI)
Record number
48020
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