Document (#23697)

Author

Kwok, K.L.

Title

¬A network approach to probabilistic information retrieval

Source

ACM transactions on information systems. 13(1995) no.3, S.324-353

Year

1995

Abstract

Shows how probabilistic information retrieval based on document components may be implemented as a feedforward (feedbackward) artificial neural network. The network supports adaptation of connection weights as well as the growing of new edges between queries and terms based on user relevance feedback data for training, and it reflects query modification and expansion in information retrieval. A learning rule is applied that can also be viewed as supporting sequential learning using a harmonic sequence learning rate. Experimental results with 4 standard small collections and a large Wall Street Journal collection show that small query expansion levels of about 30 terms can achieve most of the gains at the low-recall high-precision region, while larger expansion levels continue to provide gains at the high-recall low-precision region of a precision recall curve

Theme

Retrievalalgorithmen
Semantisches Umfeld in Indexierung u. Retrieval
Retrievalstudien

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