Document (#25039)

Author

Xu, J.
Croft, W.B.

Title

Topic-based language models for distributed retrieval

Source

Advances in information retrieval: Recent research from the Center for Intelligent Information Retrieval. Ed.: W.B. Croft

Imprint

Boston, MA : Kluwer Academic Publ.

Year

2000

Pages

S.151-172

Series

The Kluwer international series on information retrieval; 7

Abstract

Effective retrieval in a distributed environment is an important but difficult problem. Lack of effectiveness appears to have two major causes. First, existing collection selection algorithms do not work well on heterogeneous collections. Second, relevant documents are scattered over many collections and searching a few collections misses many relevant documents. We propose a topic-oriented approach to distributed retrieval. With this approach, we structure the document set of a distributed retrieval environment around a set of topics. Retrieval for a query involves first selecting the right topics for the query and then dispatching the search process to collections that contain such topics. The content of a topic is characterized by a language model. In environments where the labeling of documents by topics is unavailable, document clustering is employed for topic identification. Based on these ideas, three methods are proposed to suit different environments. We show that all three methods improve effectiveness of distributed retrieval

Theme

Verteilte bibliographische Datenbanken

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5. Jörgensen, C.: Unlocking the museum : a manifesto (2004) 0.24

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