Accession Number:

ADP007177

Title:

The Relevance Density Method for Multi-Topic Queries in Information Retrieval,

Descriptive Note:

Corporate Author:

BELL COMMUNICATIONS RESEARCH INC RED BANK NJ

Personal Author(s):

• Kane-Esrig, Y.
• Streeter, L.
• Dumais, S.
• Keese, W.
• Casella, G.

Report Date:

1992-01-01

Pagination or Media Count:

4.0

Abstract:

A long standing problem in information retrieval is how to treat queries that are best answered by two or more distinct sets of documents. Existing methods average across the words or terms in a users query, and consequently, perform poorly with multimodal queries, such as Show me documents about French art and American jazz . We propose a new method, the Relevance Density Method for selecting documents relevant to a users query. The method can be used whenever the documents and the terms are represented by vectors in a multi-dimensional space, such that the vectors corresponding to documents and terms dealing with closely related topics are close to each other. We show that the Relevance Density Method performs better for multimodal as well as single mode queries than an averaging method. In addition, we show that retrieval is substantially faster for the new method.

Descriptors:

• *INFORMATION RETRIEVAL
• ADDITION
• DENSITY
• DOCUMENTS

Subject Categories:

• Information Science

Distribution Statement:

APPROVED FOR PUBLIC RELEASE