Document (#33036)

Author

Desai, M.
Spink, A.

Title

¬A algorithm to cluster documents based on relevance

Source

Information processing and management. 41(2005) no.5, S.1035-1050

Year

2005

Abstract

Search engines fail to make a clear distinction between items of varying relevance when presenting search results to users. Instead, they rely on the user of the system to estimate which items are relevant, partially relevant, or not relevant. The user of the system is given the task of distinguishing between documents that are relevant to different degrees. This process often hinders the accessibility of relevant or partially relevant documents, particularly when the results set is large and documents of varying relevance are scattered throughout the set. In this paper, we present a clustering scheme that groups documents within relevant, partially relevant, and not relevant regions for a given search. A clustering algorithm accomplishes the task of clustering documents based on relevance. The clusters were evaluated by end-users issuing categorical, interval, and descriptive relevance judgments for the documents returned from a search. The degree of overlap between users and the system for each of the clustered regions was measured to determine the overall effectiveness of the algorithm. This research showed that clustering documents on the Web by regions of relevance is highly necessary and quite feasible.

Theme

Retrievalalgorithmen

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5. Lihui, C.; Lian, C.W.: Using Web structure and summarisation techniques for Web content mining (2005) 0.25

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