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Author: Hongyan Ma

Affiliation: Florida State University, United States

Keyword(s): Web searching, Relevance feedback, Probabilistic model, Log mining.

Related Ontology Subjects/Areas/Topics: Searching and Browsing ; Web Information Systems and Technologies ; Web Interfaces and Applications

Abstract: With the increased use of Web search engines, acute needs evolve for more adaptive and more personalizable Information Retrieval (IR) systems. This study proposes an innovative probabilistic method exploiting search logs to gather useful data about contexts and users to support adaptive retrieval. Real users’ search logs from an operational Web search engine, Infocious, were processed to obtain past queries and click-through data for adaptive indexing and unified probabilistic retrieval. An empirical experiment of retrieval effectiveness was conducted. The results demonstrate that the log-based probabilistic system yields statistically superior performance over the baseline system.

CC BY-NC-ND 4.0

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Paper citation in several formats:
Ma, H. (2009). IMPROVING WEB SEARCH BY EXPLOITING SEARCH LOGS. In Proceedings of the Fifth International Conference on Web Information Systems and Technologies - WEBIST; ISBN 978-989-8111-81-4; ISSN 2184-3252, SciTePress, pages 208-216. DOI: 10.5220/0001843802080216

@conference{webist09,
author={Hongyan Ma.},
title={IMPROVING WEB SEARCH BY EXPLOITING SEARCH LOGS},
booktitle={Proceedings of the Fifth International Conference on Web Information Systems and Technologies - WEBIST},
year={2009},
pages={208-216},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001843802080216},
isbn={978-989-8111-81-4},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the Fifth International Conference on Web Information Systems and Technologies - WEBIST
TI - IMPROVING WEB SEARCH BY EXPLOITING SEARCH LOGS
SN - 978-989-8111-81-4
IS - 2184-3252
AU - Ma, H.
PY - 2009
SP - 208
EP - 216
DO - 10.5220/0001843802080216
PB - SciTePress