An Augmented Tagging Scheme with Triple Tagging and Collective Filtering

• Published in: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence pp. 35 - 38
• Main Authors: Yang, Jie, Matsuo, Yutaka, Ishizuka, Mitsuru
• Format: Conference Proceeding
• Language: English
• Published: Washington, DC, USA IEEE Computer Society 02.11.2007
• Series: ACM Conferences
• Subjects: Human-centered computing > Collaborative and social computing; Information systems > Data management systems > Database design and models; Information systems > Data management systems > Database design and models > Data model extensions; Information systems > Information retrieval > Document representation; Information systems > Information retrieval > Evaluation of retrieval results; Information systems > Information retrieval > Retrieval models and ranking; Information systems > Information retrieval > Retrieval tasks and goals > Document filtering; Information systems > Information retrieval > Retrieval tasks and goals > Information extraction
• ISBN: 0769530265; 9780769530260
• DOI: 10.1109/WI.2007.16

Collaborative tagging is increasingly drawing attentions. However the keyword based tagging scheme has its limitations and it can be observed that tagging society are seeking and using new tagging patterns. This paper proposes a subject-predicate-object scheme for users to triple tag web resources. We first introduce the triple tag model and discuss its relations with existing tag schema and RDF model. Then a filter-based framework that supports the query of triple tags is proposed. The implementation and a case study in the comparison shopping domain are exhibited.