Web Information Organization Using Keyword Distillation Based Clustering

• Published in: 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Vol. 1; pp. 325 - 330
• Main Authors: Shibata, Tomohide, Bamba, Yasuo, Shinzato, Keiji, Kurohashi, Sadao
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 2009; IEEE
• Series: ACM Conferences
• Subjects: clustering; Clustering methods; Computing methodologies > Artificial intelligence > Knowledge representation and reasoning; Computing methodologies > Machine learning > Learning paradigms > Unsupervised learning > Cluster analysis; Conferences; Data mining; Educational products; Grid computing; Information systems > Information retrieval; Information systems > Information retrieval > Evaluation of retrieval results; Intelligent agent; keyword unification; Navigation; open search engine; Search engines; Web pages; clustering; open search engine; keyword unification
• ISBN: 0769538010; 9780769538013
• DOI: 10.1109/WI-IAT.2009.57

This paper describes a system that conducts search result clustering for several thousands of Web pages, and elaborates cluster labels through keyword distillation. Keyword distillation is a method that properly handles spelling variations, transliterations, synonyms, inclusion relations and word ambiguity, using linguistic resources and contexts of a user's query. The system provides a clustering result from 1,000 pages in less than one minute by taking advantage of a search engine infrastructure and grid computing environment. Experimental results show that the system correctly merged synonymous keywords and is useful for finding topics hidden in the lower-ranked pages in a search result.