APPLYING CROSS-TOPIC RELATIONSHIPS TO INCREMENTAL RELEVANCE FEEDBACK

Terry C H Lai; Stephen C F Chan; Korris F L Chung

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Paper

APPLYING CROSS-TOPIC RELATIONSHIPS TO INCREMENTAL RELEVANCE FEEDBACK

Topics: Web Databases

In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: ICEIS, 356-363, 2004 , Porto, Portugal

Authors: Terry C H Lai ; Stephen C F Chan and Korris F L Chung

Affiliation: The Hong Kong Polytechnic University, China

Keyword(s): Internet Information Retrieval, Search Topics, Bayesian Networks

Related Ontology Subjects/Areas/Topics: Databases and Information Systems Integration ; Enterprise Information Systems ; Web Databases

Abstract: General purpose search engines like Google and Yahoo define search topics for the purpose of document organization, yet their hierarchical structures cover only a portion of topic relationships. Search effectiveness can be improved by using search topic networks, in which topics are linked through semantic relations. In our search model, is-child and is-neighbor relations are defined as relations among search topics, which in turn can serve as search techniques; the is-child relation allows searching from general concepts, while the is-neighbor relation provides fresh information that can help users to identify search areas. This search model uses the Bayesian Networks and the incremental relevance feedback. Our experiments show that search models using the Bayesian Networks and the incremental relevance feedback improve search effectiveness.

CC BY-NC-ND 4.0

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Paper citation in several formats:

C H Lai, T.; C F Chan, S. and F L Chung, K. (2004). APPLYING CROSS-TOPIC RELATIONSHIPS TO INCREMENTAL RELEVANCE FEEDBACK. In Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 972-8865-00-7; ISSN 2184-4992, SciTePress, pages 356-363. DOI: 10.5220/0002620203560363

@conference{iceis04,
author={Terry {C H Lai}. and Stephen {C F Chan}. and Korris {F L Chung}.},
title={APPLYING CROSS-TOPIC RELATIONSHIPS TO INCREMENTAL RELEVANCE FEEDBACK},
booktitle={Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2004},
pages={356-363},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002620203560363},
isbn={972-8865-00-7},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Sixth International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - APPLYING CROSS-TOPIC RELATIONSHIPS TO INCREMENTAL RELEVANCE FEEDBACK
SN - 972-8865-00-7
IS - 2184-4992
AU - C H Lai, T.
AU - C F Chan, S.
AU - F L Chung, K.
PY - 2004
SP - 356
EP - 363
DO - 10.5220/0002620203560363
PB - SciTePress