Information Retrieval: A Survey

Information Retrieval: A Survey

This report provides a good overview of Information Retrieval (IR), both commercial practice and research. More specifically, it deals with the retrieval of unstructured and semi-structured text documents or messages.

Publication date: 30 Nov 2000

ISBN-10: n/a

ISBN-13: n/a

Paperback: n/a

Views: 16,541

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Post time: 21 Jun 2007 03:46:54

Information Retrieval: A Survey

Information Retrieval: A Survey This report provides a good overview of Information Retrieval (IR), both commercial practice and research. More specifically, it deals with the retrieval of unstructured and semi-structured text documents or messages.
Tag(s): Digital Libraries
Publication date: 30 Nov 2000
ISBN-10: n/a
ISBN-13: n/a
Paperback: n/a
Views: 16,541
Document Type: N/A
Publisher: n/a
License: n/a
Post time: 21 Jun 2007 03:46:54
Excerpts from the Abstract:

Information Retrieval (IR) is the discipline that deals with retrieval of unstructured data, especially textual documents, in response to a query or topic statement, which may itself be unstructured, e.g., a sentence or even another document, or which may be structured, e.g., a boolean expression. The need for effective methods of automated IR has grown in importance because of the tremendous explosion in the amount of unstructured data, both internal, corporate document collections, and the immense and growing number of document sources on the Internet.

This report is a tutorial and survey of the state of the art (ed: this report was published in 2000), both research and commercial, in this dynamic field. The topics covered include: formulation of structured and unstructured queries and topic statements, indexing (including term weighting) of document collections, methods for computing the similarity of queries and documents, classification and routing of documents in an incoming stream to users on the basis of topic or need statements, clustering of document collections on the basis of language or topic, and statistical, probabilistic, and semantic methods of analyzing and retrieving documents.




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Ed Greengrass

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