Multinomial randomness models for retrieval with document fields

Plachouras, V. and Ounis, I. (2007) Multinomial randomness models for retrieval with document fields. Lecture Notes in Computer Science, 4425, pp. 28-39. (doi: 10.1007/978-3-540-71496-5_6)

Abstract

Document fields, such as the title or the headings of a document, offer a way to consider the structure of documents for retrieval. Most of the proposed approaches in the literature employ either a linear combination of scores assigned to different fields, or a linear combination of frequencies in the term frequency normalisation component. In the context of the Divergence From Randomness framework, we have a sound opportunity to integrate document fields in the probabilistic randomness model. This paper introduces novel probabilistic models for incorporating fields in the retrieval process using a multinomial randomness model and its information theoretic approximation. The evaluation results from experiments conducted with a standard TREC Web test collection show that the proposed models perform as well as a state-of-the-art field-based weighting model, while at the same time, they are theoretically founded and more extensible than current field-based models.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Ounis, Professor Iadh
• Authors: Plachouras, V., and Ounis, I.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Lecture Notes in Computer Science
• Publisher: Springer
• ISSN: 1611-3349
• Copyright Holders: Copyright © 2007 Springer
• First Published: First published in Lecture Notes in Computer Science 4425:28-39
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher.