It is crucial for information retrieval systems to learn more about what users search for in order to fulfil the intent of searches. This paper introduces query taxonomy generation, which attempts to organise users’ queries into a hierarchical structure of topic classes. Such a query taxonomy provides a basis for the in‐depth analysis of users’ queries on a larger scale and can benefit many information retrieval systems. The proposed approach to this problem consists of two computational processes: hierarchical query clustering to generate a query taxonomy from scratch, and query categorisation to place newly‐arrived queries into the taxonomy. The results of the preliminary experiment have shown the potential of the proposed approach in generating taxonomies for queries, which may be useful in various Web information retrieval applications.
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1 August 2003
Research Article|
August 01 2003
Automatic query taxonomy generation for information retrieval applications Available to Purchase
Shui‐Lung Chuang;
Shui‐Lung Chuang
Shui‐Lung Chuang is a Research Associate at the Institute of Information Science, Academia Sinica, Taipei, Taiwan.
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Lee‐Feng Chien
Lee‐Feng Chien
Lee‐Feng Chien is a Research Fellow, at the Institute of Information Science, Academia Sinica, Taipei, Taiwan.
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Publisher: Emerald Publishing
Online ISSN: 1468-4535
Print ISSN: 1468-4527
© MCB UP Limited
2003
Online Information Review (2003) 27 (4): 243–255.
Citation
Chuang S, Chien L (2003), "Automatic query taxonomy generation for information retrieval applications". Online Information Review, Vol. 27 No. 4 pp. 243–255, doi: https://doi.org/10.1108/14684520310489032
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