Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/40759
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dc.titleField Similarity Algorithm
dc.contributor.authorYang, Q.X.
dc.contributor.authorYuan, S.S.
dc.contributor.authorLuchun
dc.contributor.authorZhao, L.
dc.contributor.authorPeng, S.
dc.date.accessioned2013-07-04T08:11:40Z
dc.date.available2013-07-04T08:11:40Z
dc.date.issued2002
dc.identifier.citationYang, Q.X.,Yuan, S.S.,Luchun,Zhao, L.,Peng, S. (2002). Field Similarity Algorithm. Proceedings of the Joint Conference on Information Sciences 6 : 432-436. ScholarBank@NUS Repository.
dc.identifier.isbn0970789017
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/40759
dc.description.abstractThe introduction of a new algorithm, Moving Contracting Window Pattern Algorithm (MCWPA), to calculate Field Similarity was discussed. The algorithm overcame some drawbacks that existed in the previous algorithm of the Field Similarity. In the previous algorithm, the adoption of word as basic unit resulted in its inability to distinguish between two exactly same fields and two fields with the same words in different sequences. MCWPA used the character as the unit in order to improve the accuracy. In terms of false detection, MCWPA performed much better than the previous algorithm.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleProceedings of the Joint Conference on Information Sciences
dc.description.volume6
dc.description.page432-436
dc.identifier.isiutNOT_IN_WOS
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