QUT ePrints

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)

View at publisher

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.

Impact and interest:

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

72 since deposited on 04 Sep 2011
9 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

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

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page