文章基本信息

标题：Optimized Clustering for Personal Name Information Extraction
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作者：G. Naveen Sundar ; Teena A. Sunny
期刊名称：International Journal of Computer Science & Technology
印刷版ISSN：2229-4333
电子版ISSN：0976-8491
出版年度：2012
卷号：3
期号：4
页码：361-363
语种：English
出版社：Ayushmaan Technologies
摘要：The person name information extraction system generally mines the person in query and their specific personal featured information(occupation, DOBetc). One issue anticipated in such system includes ambiguity of person names and feature extractions. To resolve this issue we employ agglomerative clustering that that will cluster features that share a similarity matrix and thus helps to find the target person and relevant personal details.This paper clearly portrays how this clustering technique is an effective measure amongst other.
关键词：Unsupervised learning;Fscore;Ambiguity;Bigrams;Log Likelihood