PUMA publications for /author/Zhichen%20Xu/diploma_thesishttps://puma.uni-kassel.de/author/Zhichen%20Xu/diploma_thesisPUMA RSS feed for /author/Zhichen%20Xu/diploma_thesis2024-03-28T21:00:13+01:00Towards the Semantic Web: Collaborative Tag Suggestionshttps://puma.uni-kassel.de/bibtex/249719d13c6da0c5f6917b97ef777184e/benzbenz2011-02-04T16:09:36+01:00tagging ol_web2.0 closely_related diploma_thesis folksonomy emergentsemantics_evidence <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Zhichen Xu" itemprop="url" href="/author/Zhichen%20Xu"><span itemprop="name">Z. Xu</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Yun Fu" itemprop="url" href="/author/Yun%20Fu"><span itemprop="name">Y. Fu</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jianchang Mao" itemprop="url" href="/author/Jianchang%20Mao"><span itemprop="name">J. Mao</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Difu Su" itemprop="url" href="/author/Difu%20Su"><span itemprop="name">D. Su</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the Collaborative Web Tagging Workshop at the WWW 2006</span>, </em></span><em>Edinburgh, Scotland, </em>(<em><span>Mai 2006<meta content="Mai 2006" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:36 CET 2011Edinburgh, ScotlandProceedings of the Collaborative Web Tagging Workshop at the WWW 2006MayTowards the Semantic Web: Collaborative Tag Suggestions2006tagging ol_web2.0 closely_related diploma_thesis folksonomy emergentsemantics_evidence Content organization over the Internet went through several interesting phases of evolution: from structured directories to unstructured Web search engines and more recently, to tagging as a way for aggregating information, a step towards the semantic web vision. Tagging allows ranking and data organization to directly utilize inputs from end users, enabling machine processing of Web content. Since tags are created by individual users in a free form, one important problem facing tagging is to identify most appropriate tags, while eliminating noise and spam. For this purpose, we define a set of general criteria for a good tagging system. These criteria include high coverage of multiple facets to ensure good recall, least effort to reduce the cost involved in browsing, and high popularity to ensure tag quality. We propose a collaborative tag suggestion algorithm using these criteria to spot high-quality tags. The proposed algorithm employs a goodness measure for tags derived from collective user authorities to combat spam. The goodness measure is iteratively adjusted by a reward-penalty algorithm, which also incorporates other sources of tags, e.g., content-based auto-generated tags. Our experiments based on My Web 2.0 show that the algorithm is effective.