Exploiting Tag Relations to Improve Search in Collaborative Tagging Systems

被引：0

作者：

Lin, Huairen ^{[1
]}

Davis, Joseph ^{[1
]}

机构：

[1] Univ Sydney, Sch IT, Knowledge Discovery & Management Res Grp, Sydney, NSW, Australia

来源：

2010 IEEE FOURTH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC 2010) | 2010年

关键词：

tagging; semantic search; tag relateness;

D O I：

10.1109/ICSC.2010.13

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The main problem of tag-based search in collaborative tagging system (CTS) is the lack of explicit semantic relations between tags. To address this problem, we propose an approach based on the integration of symmetrical and asymmetrical similarity measures to calibrate the relatedness between tags and then further organize them into an ontological structure. We also demonstrate how this extracted knowledge will help to apply semantic web techniques to existing web2.0 applications such as CTS and improve their search and browse capabilities.

引用

页码：442 / 443

页数：2

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