Conference proceeding
Using associate constraint network with forward evaluation to overcome cross-lingual semantic interoperability challenge for crime information extraction
2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, v 2, pp 1125-1130
01 Jan 2006
Abstract
Information extraction is important for crime analysis. Due to the popularity of the Web, information related to crime and terrorism is available in multiple languages. As a result, cross-lingual semantic interoperability is essential when we extract information across multiple languages. In our previous work, we have developed several techniques to generate an automatic cross-lingual thesaurus to support cross-lingual information retrieval based on a parallel corpus collected from the Web. The techniques include Hopfield network and associate constraint network with backmarking. Although these techniques obtain satisfactory performance, they have weaknesses in efficiency, consistency, precision or recall. In this work, we develop a new searching technique, namely forward evaluation, on the basis of our previously developed associate constraint network model. We have conducted an experiment and show that the proposed forward evaluation technique outperforms both Hopfield network and associate constraint network with backmarking in terms of precision and recall. In addition, its efficiency is better than Hopfield network but is not as good as associate constraint network with backmarking.
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Details
- Title
- Using associate constraint network with forward evaluation to overcome cross-lingual semantic interoperability challenge for crime information extraction
- Creators
- Christopher C. Yang - Chinese University of Hong KongChih-Ping Wei - National Tsing Hua UniversityKar Wing Li - City University of Hong Kong
- Publication Details
- 2006 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-6, PROCEEDINGS, v 2, pp 1125-1130
- Series
- IEEE International Conference on Systems Man and Cybernetics Conference Proceedings
- Publisher
- IEEE
- Number of pages
- 2
- Grant note
- 4335/02E / Hong Kong Research Grant Council; Hong Kong Research Grants Council 2050268 / Direct Research Grant of the Chinese University of Hong Kong
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Information Science
- Web of Science ID
- WOS:000248078501038
- Scopus ID
- 2-s2.0-34548142607
- Other Identifier
- 991021855281004721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Automation & Control Systems
- Computer Science, Artificial Intelligence
- Computer Science, Cybernetics