Ontology learning from user tagging for recommendation making
Djuana, Endang, Xu, Yue, Li, Yuefeng, & Josang, Audun (2011) Ontology learning from user tagging for recommendation making. In Maret, Pierre, Vercouter, Laurent, & Morr, Christo El (Eds.) Proceedings of 3rd International Workshop on Web Intelligence & Communities, IEEE, Lyon, France. (In Press)
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Abstract
Recently, user tagging systems have grown in popularity on the web. The tagging process is quite simple for ordinary users, which contributes to its popularity. However, free vocabulary has lack of standardization and semantic ambiguity. It is possible to capture the semantics from user tagging into some form of ontology, but the application of the resulted ontology for recommendation making has not been that flourishing. In this paper we discuss our approach to learn domain ontology from user tagging information and apply the extracted tag ontology in a pilot tag recommendation experiment. The initial result shows that by using the tag ontology to re-rank the recommended tags, the accuracy of the tag recommendation can be improved.
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| ID Code: | 45682 |
|---|---|
| Item Type: | Conference Paper |
| Additional Information: | Web Intelligence is a multidisciplinary area dealing with exploiting data and services over the Web, to create new data and services using Information and Communication Technologies (ICT) and Artificial Intelligence (AI) techniques. The link to Networking and Virtual Communities (VCs) is obvious: the web is a set of nodes, providing and consuming data and services; the permanent or temporary ties and exchanges in-between these nodes build the so-called virtual communities; and the ICT and AI techniques contribute to the process and automate (or partly automate) communication and cooperation processes. The workshop provides presentation and discussion opportunities for researchers working on web intelligence applied to collaborative networks, such as virtual communities. The possibilities and consequences of the web usage for collaborative networks are tremendous and new tools are required to satisfy users and service providers. Thus, Web Intelligence brings new research problems related to information and service access, quality of service, personalization, privacy preserving, trust as well as other issues. |
| Keywords: | collaborative tagging, ontology learning, tag recommendation |
| Subjects: | Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704) Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Organisation of Information and Knowledge Resources (080707) Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Social and Community Informatics (080709) |
| Divisions: | Past > Schools > Computer Science Past > QUT Faculties & Divisions > Faculty of Science and Technology |
| Copyright Owner: | Copyright 2011 IEEE |
| Copyright Statement: | Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE |
| Deposited On: | 05 Sep 2011 09:47 |
| Last Modified: | 06 Sep 2011 06:26 |
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