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Semantic information retrieval research based on co-occurrence analysis

Wen Lou (School of Information Management, Wuhan University, Wuhan, People's Republic of China)
Junping Qiu (School of Information Management, Wuhan University, Wuhan, People's Republic of China)

Online Information Review

ISSN: 1468-4527

Article publication date: 8 January 2014

982

Abstract

Purpose

The paper aims to develop a new method for potential relations retrieval. It aims to find common aspects between co-occurrence analysis and ontology to build a model of semantic information retrieval based on co-occurrence analysis.

Design/methodology/approach

This paper used a literature review, co-occurrence analysis, ontology build and other methods to design a model and process of semantic information retrieval based on co-occurrence analysis. Archaeological data from Wuhan University Library's bibliographic retrieval systems was used for experimental analysis.

Findings

The literature review found that semantic information retrieval research mainly concentrates on ontology-based query techniques, semantic annotation and semantic relation retrieval. Moreover most recent systems can only achieve obvious relations retrieval. Ontology and co-occurrence analysis have strong similarities in theoretical ideas, data types, expressions, and applications.

Research limitations/implications

The experiment data came from a Chinese university which perhaps limits its usefulness elsewhere.

Practical implications

This paper constructed a model to understand potential relations retrieval. An experiment proved the feasibility of co-occurrence analysis used in semantic information retrieval. Compared with traditional retrieval, semantic information retrieval based on co-occurrence analysis is more user-friendly.

Originality/value

This study is one of the first to combine co-occurrence analysis with semantic information retrieval to find detailed relationships.

Keywords

Acknowledgements

This paper was supported by a major programme of the National Social Science Foundation of China, “Semantic-based Deep Integration and Visualisation of Library Resources” (11&ZD152). The authors would like to thank Fan Yu and Yuan Hu for their suggestions and support.

Citation

Lou, W. and Qiu, J. (2014), "Semantic information retrieval research based on co-occurrence analysis", Online Information Review, Vol. 38 No. 1, pp. 4-23. https://doi.org/10.1108/OIR-11-2012-0203

Publisher

:

Emerald Group Publishing Limited

Copyright © 2014, Emerald Group Publishing Limited

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