基于潜在语义分析的Deep Web查询接口聚类研究

计算机科学 ›› 2013, Vol. 40 ›› Issue (11): 228-230.

基于潜在语义分析的Deep Web查询接口聚类研究

强保华,李巍,邹显春,汪天天,吴春明

桂林电子科技大学计算机科学与工程学院广西541000;桂林电子科技大学计算机科学与工程学院广西541000;西南大学计算机与信息科学学院重庆400715;桂林电子科技大学计算机科学与工程学院广西541000;西南大学计算机与信息科学学院重庆400715

出版日期:2018-11-16 发布日期:2018-11-16
基金资助:
本文受国家自然科学基金(61163057),广西自然科学基金(2012jjAAG0063),广西可信软件重点实验室开放基金(KX201117),广西研究生科研创新项目(YCSZ2012070)资助

Research on Deep Web Query Interface Clustering Based on Latent Semantic Analysis

QIANG Bao-hua,LI Wei,ZOU Xian-chun,WANG Tian-tian and WU Chun-ming

Online:2018-11-16 Published:2018-11-16

摘要/Abstract

摘要： 集成查询接口的生成是Deep Web数据集成的重要组成环节。如何对不同领域的查询接口进行有效的聚类是生成集成查询接口时需要解决的核心问题之一。针对传统的向量空间模型在Deep Web查询接口聚类时单纯依赖关键词匹配的缺点,引入潜在语义分析(LSA)的方法来发掘查询接口之间的语义关系,并给出了基于潜在语义分析的Deep Web查询接口聚类算法,最后采用UIUC的Web集成资源库提供的数据进行了实验。结果表明,潜在语义分析的方法提高了同一领域查询接口之间的相似度,明显改善了Deep Web查询接口聚类的质量。

关键词: 潜在语义分析,奇异值分解,Deep Web,查询接口聚类

Abstract: Generation of integrated query interfaces is the important issue of Deep Web data integration．How to cluster different query interfaces effectively is one of the most core issues when generating integrated query interface．Due to the traditional vector space model can’t solve the shortage of relying on keyword maching in the Deep Web query interface clustering,the Latent Semantic Analysis (LSA) method was introduced and then the algorithm of Deep Web query interface clustering based on Latent Semantic Analysis was proposed．The experimental results on UIUC Web integration repository show that LSA method can significantly improve the performance of Deep Web query interface clustering.

Key words: Latent semantic analysis,Singular value decomposition,Deep Web,Query interface clustering

强保华,李巍,邹显春,汪天天,吴春明. 基于潜在语义分析的Deep Web查询接口聚类研究[J]. 计算机科学, 2013, 40(11): 228-230. https://doi.org/

QIANG Bao-hua,LI Wei,ZOU Xian-chun,WANG Tian-tian and WU Chun-ming. Research on Deep Web Query Interface Clustering Based on Latent Semantic Analysis[J]. Computer Science, 2013, 40(11): 228-230. https://doi.org/

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