Co-Clustering Tags and Social Data Sources

摘要：

Under social tagging systems, a typical Web 2.0 application, users label digital data sources by using freely chosen textual descriptions (tags). Poor retrieval in the aforementioned systems remains a major problem mostly due to questionable tag validity and tag ambiguity. Earlier clustering techniques have shown limited improvements, since they were based mostly on tag co-occurrences. In this paper, a co-clustering approach is employed, that exploits joint groups of related tags and social data sources, in which both social and semantic aspects of tags are considered simultaneously. Experimental results demonstrate the ef.-ciency and the bene.cial outcome of the proposed approach in correlating relevant tags and resources.

作者: Eirini Giannakidou Vassiliki Koutsonikola Athena Vakali Ioannis Kompatsiaris

作者单位: Department of Informatics Aristotle University 54124 Thessaloniki,Greece Informatics and Telematics Institute CERTH　Thermi-Thessaloniki,Greece

会议类型: 国际会议

会议名称: The Ninth International Conference on Web-Age Information Management(第九届web时代信息管理国际会议)(WAIM 2008)

会议地点: 张家界

会议语种:英文

在线出版日期: 2008-07-20（万方平台首次上网日期，不代表论文的发表时间）