A framework for long‐term learning of topical user preferences in information retrieval-Reference-Cited by-同舟云学术

A framework for long‐term learning of topical user preferences in information retrieval

Published:2004-05-01 Issue:5/6 Volume:105 Page:184-195
ISSN:0307-4803
Container-title:New Library World
language:en
Short-container-title:

Author:

Mandl Thomas,Womser‐Hacker Christa

Abstract

A framework for the long‐term learning of user preferences in information retrieval is presented. The multiple indexing and method‐object relations (MIMOR) model tightly integrates a fusion method and a relevance feedback processor into a learning model. Several black box matching functions can be combined into a linear combination committee machine which reflects the user's vague individual cognitive concepts expressed in relevance feedback decisions. An extension based on the soft computing paradigm couples the relevance feedback processor and the matching function into a unified retrieval system.

Publisher

Emerald

Subject

Library and Information Sciences

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