PUMA publications for /tag/ontologyhttps://puma.uni-kassel.de/tag/ontologyPUMA RSS feed for /tag/ontology2024-03-19T02:37:55+01:00Metadata Mechanisms: From Ontology to Folksonomy ... and Backhttps://puma.uni-kassel.de/bibtex/2efc1396e845f3db1688dc8ef154d9520/benzbenz2011-02-04T16:09:43+01:00ol_web2.0 semantic_web tagging faceted_classification folksonomy_background folksonomy diploma_thesis ontology <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stijn Christiaens" itemprop="url" href="/author/Stijn%20Christiaens"><span itemprop="name">S. Christiaens</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Lecture Notes in Computer Science: On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops</span>, </em><em><span itemprop="publisher">Springer</span>, </em></span>(<em><span>2006<meta content="2006" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:43 CET 2011Lecture Notes in Computer Science: On the Move to Meaningful Internet Systems 2006: OTM 2006 WorkshopsMetadata Mechanisms: From Ontology to Folksonomy ... and Back2006ol_web2.0 semantic_web tagging faceted_classification folksonomy_background folksonomy diploma_thesis ontology In this paper we give a brief overview of different metadata mechanisms (like ontologies and folksonomies) and how they relate to each other. We identify major strengths and weaknesses of these mechanisms. We claim that these mechanisms can be classified from restricted (e.g., ontology) to free (e.g., free text tagging). In our view, these mechanisms should not be used in isolation, but rather as complementary solutions, in a continuous process wherein the strong points of one increase the semantic depth of the other. We give an overview of early active research already going on in this direction and propose that methodologies to support this process be developed. We demonstrate a possible approach, in which we mix tagging, taxonomy and ontology.Bridging ontologies and folksonomies to leverage knowledge sharing on the social Web: A brief surveyhttps://puma.uni-kassel.de/bibtex/29372f9c2db8b9f4cf05b3db84e6589ac/benzbenz2011-02-04T16:09:41+01:00folksonomy ontology ol_web2.0 overview <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Freddy Limpens" itemprop="url" href="/author/Freddy%20Limpens"><span itemprop="name">F. Limpens</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Fabien Gandon" itemprop="url" href="/author/Fabien%20Gandon"><span itemprop="name">F. Gandon</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michel Buffa" itemprop="url" href="/author/Michel%20Buffa"><span itemprop="name">M. Buffa</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Automated Software Engineering - Workshops, 2008. ASE Workshops 2008. 23rd IEEE/ACM International Conference on</em></span></span> </span>(<em><span>September 2008<meta content="September 2008" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:41 CET 2011Automated Software Engineering - Workshops, 2008. ASE Workshops 2008. 23rd IEEE/ACM International Conference onSept.13-18Bridging ontologies and folksonomies to leverage knowledge sharing on the social Web: A brief survey2008folksonomy ontology ol_web2.0 overview Social tagging systems have recently became very popular as a means to classify large sets of resources shared among on-line communities over the social Web. However, the folksonomies resulting from the use of these systems revealed limitations : tags are ambiguous and their spelling may vary, and folksonomies are difficult to exploit in order to retrieve or exchange information. This article compares the recent attempts to overcome these limitations and to support the use of folksonomies with formal languages and ontologies from the Semantic Web.Welcome to IEEE Xplore 2.0: Bridging ontologies and folksonomies to leverage knowledge sharing on the social Web: A brief surveyFrom folksonomies to ontologies: employing wisdom of the crowds to serve learning purposeshttps://puma.uni-kassel.de/bibtex/2dd5cdcc6449d97622033bbebcd4d1874/benzbenz2011-02-04T16:09:41+01:002xyz folksonomy learning ontology tagging ol_web2.0 background <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mathias Lux" itemprop="url" href="/author/Mathias%20Lux"><span itemprop="name">M. Lux</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gisela Dösinger" itemprop="url" href="/author/Gisela%20D%c3%b6singer"><span itemprop="name">G. Dösinger</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>International Journal of Knowledge and Learning</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">3 </span></span>(<span itemprop="issueNumber">4-5</span>):
<span itemprop="pagination">515--528</span></em> </span>(<em><span>Januar 2008<meta content="Januar 2008" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:41 CET 2011International Journal of Knowledge and Learningjan4-5515--528From folksonomies to ontologies: employing wisdom of the crowds to serve learning purposes320082xyz folksonomy learning ontology tagging ol_web2.0 background Is Web 2.0 just hype or just a buzzword, which might disappear in the near future One way to find answers to these questions is to investigate the actual benefit of the Web 2.0 for real use cases. Within this contribution we study a very special aspect of the Web 2.0 the folksonomy and its use within self-directed learning. Guided by conceptual principles of emergent computing we point out methods, which might be able to let semantics emerge from folksonomies and discuss the effect of the results in self-directed learning.Towards ontology learning from folksonomieshttps://puma.uni-kassel.de/bibtex/27b335f08a288a79eb70eff89f1ec7630/benzbenz2011-02-04T16:09:39+01:00folksonomy ontology toread ol_web2.0 toread_dbe methods_concepts methods_concepthierarchy <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jie Tang" itemprop="url" href="/author/Jie%20Tang"><span itemprop="name">J. Tang</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Ho fung Leung" itemprop="url" href="/author/Ho%20fung%20Leung"><span itemprop="name">H. fung Leung</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Qiong Luo" itemprop="url" href="/author/Qiong%20Luo"><span itemprop="name">Q. Luo</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Dewei Chen" itemprop="url" href="/author/Dewei%20Chen"><span itemprop="name">D. Chen</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jibin Gong" itemprop="url" href="/author/Jibin%20Gong"><span itemprop="name">J. Gong</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">IJCAI'09: Proceedings of the 21st international jont conference on Artifical intelligence</span>, </em></span><em>Seite <span itemprop="pagination">2089--2094</span>. </em><em>San Francisco, CA, USA, </em><em><span itemprop="publisher">Morgan Kaufmann Publishers Inc.</span>, </em>(<em><span>2009<meta content="2009" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:39 CET 2011San Francisco, CA, USAIJCAI'09: Proceedings of the 21st international jont conference on Artifical intelligence2089--2094Towards ontology learning from folksonomies2009folksonomy ontology toread ol_web2.0 toread_dbe methods_concepts methods_concepthierarchy A folksonomy refers to a collection of user-defined tags with which users describe contents published on the Web. With the flourish of Web 2.0, folksonomies have become an important mean to develop the Semantic Web. Because tags in folksonomies are authored freely, there is a need to understand the structure and semantics of these tags in various applications. In this paper, we propose a learning approach to create an ontology that captures the hierarchical semantic structure of folksonomies. Our experimental results on two different genres of real world data sets show that our method can effectively learn the ontology structure from the folksonomies.Towards ontology learning from folksonomiesOntologies on Demand? - A Description of the State-of-the-Art, Applications, Challenges and Trends for Ontology Learning from Texthttps://puma.uni-kassel.de/bibtex/2fe4c2950b5be221b493e29e4339240e8/benzbenz2011-02-04T16:09:33+01:00learning ol_web2.0 ontology overview <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Philipp Cimiano" itemprop="url" href="/author/Philipp%20Cimiano"><span itemprop="name">P. Cimiano</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Johanna Völker" itemprop="url" href="/author/Johanna%20V%c3%b6lker"><span itemprop="name">J. Völker</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Rudi Studer" itemprop="url" href="/author/Rudi%20Studer"><span itemprop="name">R. Studer</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Information, Wissenschaft und Praxis</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">57 </span></span>(<span itemprop="issueNumber">6-7</span>):
<span itemprop="pagination">315-320</span></em> </span>(<em><span>Oktober 2006<meta content="Oktober 2006" itemprop="datePublished"/></span></em>)<em>see the special issue for more contributions related to the Semantic Web.</em>Fri Feb 04 16:09:33 CET 2011Information, Wissenschaft und PraxisOCTsee the special issue for more contributions related to the Semantic Web6-7315-320Ontologies on Demand? - A Description of the State-of-the-Art, Applications, Challenges and Trends for Ontology Learning from Text572006learning ol_web2.0 ontology overview Ontologies are nowadays used for many applications requiring data, services and resources in general to be interoperable and machine understandable. Such applications are for example web service discovery and composition, information integration across databases, intelligent search, etc. The general idea is that data and services are semantically described with respect to ontologies,which are formal specifications of a domain of interest, and can thus be shared and reused in a way such that the shared meaning specified by the ontology remains formally the same across different parties and applications. As the cost of creating ontologies is relatively high, different proposals have emerged for learning ontologies from structured and unstructured resources. In this article we examine the maturity of techniques for ontology learning from textual resources, addressing the question whether the state-of-the-art is mature enough to produce ontologies ‘on demand’.Institut AIFB - Publikation: Ontologies on Demand? - A Description of the State-of-the-Art, Applications, Challenges and Trends for Ontology Learning from TextCollaborative and Usage-Driven Evolution of Personal Ontologies.https://puma.uni-kassel.de/bibtex/21a8829cde1cb26241a48901e28a953d2/benzbenz2011-02-04T16:09:31+01:00bibster change_operation ol_web2.0 ontologies ontology personalized recommender widely_related <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Peter Haase" itemprop="url" href="/author/Peter%20Haase"><span itemprop="name">P. Haase</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Hotho" itemprop="url" href="/author/Andreas%20Hotho"><span itemprop="name">A. Hotho</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lars Schmidt-Thieme" itemprop="url" href="/author/Lars%20Schmidt-Thieme"><span itemprop="name">L. Schmidt-Thieme</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="York Sure" itemprop="url" href="/author/York%20Sure"><span itemprop="name">Y. Sure</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">ESWC</span>, </em></span><em>Volume 3532 von Lecture Notes in Computer Science, </em><em>Seite <span itemprop="pagination">486-499</span>. </em><em><span itemprop="publisher">Springer</span>, </em>(<em><span>2005<meta content="2005" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:31 CET 2011ESWCconf/esws/2005486-499Lecture Notes in Computer ScienceCollaborative and Usage-Driven Evolution of Personal Ontologies.35322005bibster change_operation ol_web2.0 ontologies ontology personalized recommender widely_related Large information repositories as digital libraries, online shops, etc. rely on a taxonomy of the objects under consideration to structure the vast contents and facilitate browsing and searching (e.g., ACM topic classification for computer science literature, Amazon product taxonomy, etc.). As in heterogenous communities users typically will use different parts of such an ontology with varying intensity, customization and personalization of the ontologies is desirable. Of particular interest for supporting users during the personalization are collaborative filtering systems which can produce personal recommendations by computing the similarity between own preferences and the one of other people. In this paper we adapt a collaborative filtering recommender system to assist users in the management and evolution of their personal ontology by providing detailed suggestions of ontology changes. Such a system has been implemented in the context of Bibster, a peer-to-peer based personal bibliography management tool. Finally, we report on an experiment with the Bibster community that shows the performance improvements over non-personalized recommendations.dblpThe Dynamics and Semantics of Collaborative Tagginghttps://puma.uni-kassel.de/bibtex/2266b31ad3599499aacf593e82e775c5b/benzbenz2011-02-04T16:09:30+01:00closely_related collaborative_tagging diploma_thesis ol_web2.0 ontology semantics background <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Harry Halpin" itemprop="url" href="/author/Harry%20Halpin"><span itemprop="name">H. Halpin</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Valentin Robu" itemprop="url" href="/author/Valentin%20Robu"><span itemprop="name">V. Robu</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hana Shepard" itemprop="url" href="/author/Hana%20Shepard"><span itemprop="name">H. Shepard</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 1st Semantic Authoring and Annotation Workshop (SAAW'06)</span>, </em></span>(<em><span>2006<meta content="2006" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:30 CET 2011Proceedings of the 1st Semantic Authoring and Annotation Workshop (SAAW'06)The Dynamics and Semantics of Collaborative Tagging2006closely_related collaborative_tagging diploma_thesis ol_web2.0 ontology semantics background The debate within the Web community over the optimal means by which to organize information often pits formalized classifications against distributed collaborative tagging systems. A number of questions remain unanswered, however, regarding the nature of collaborative tagging systems including the dynamics of such systems and whether coherent classification schemes can emerge from undirected tagging by users. Currently millions of users are using collaborative tagging without centrally organizing principles, and many suspect this exhibits features considered to be indicative of a complex system. If this is the case, it remains to be seem whether collaborative tagging by users over time leads to emergent classi- fication schemes that could be formalized into an ontology usable by the Semantic Web. This paper uses data from �popular� tagged sites on the social bookmarking site del.icio.us to examine the dynamics of such collaborative tagging systems. In particular, we are trying to determine whether the distribution of tag frequencies stabilizes, which indicates a degree of cohesion or consensus among users about the optimal tags to describe particular sites. We use tag co-occurrence networks for a sample domain of tags to analyze the meaning of particular tags given their relationship to other tags and automatically create an ontology. We also produce a generative model of collaborative tagging in order to model and understand some of the basic dynamics behind the process.Using WordNet to turn a folksonomy into a hierarchy of conceptshttps://puma.uni-kassel.de/bibtex/27f7ac73677841b4580461d408e83495a/benzbenz2011-02-04T16:09:29+01:00folksonomy ol_web2.0 ontology wordnet enrichment <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="David Laniado" itemprop="url" href="/author/David%20Laniado"><span itemprop="name">D. Laniado</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Davide Eynard" itemprop="url" href="/author/Davide%20Eynard"><span itemprop="name">D. Eynard</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Marco Colombetti" itemprop="url" href="/author/Marco%20Colombetti"><span itemprop="name">M. Colombetti</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Semantic Web Application and Perspectives - Fourth Italian Semantic Web Workshop</span>, </em></span><em>Seite <span itemprop="pagination">192--201</span>. </em>(<em><span>Dezember 2007<meta content="Dezember 2007" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:29 CET 2011Semantic Web Application and Perspectives - Fourth Italian Semantic Web WorkshopDec192--201Using WordNet to turn a folksonomy into a hierarchy of concepts2007folksonomy ol_web2.0 ontology wordnet enrichment As the volume of information in the read-write Web increases rapidly, folksonomies are becoming a widely used tool to organize and categorize resources in a bottom up, flat and inclusive way. However, due to their very structure, they show some drawbacks; in particular the lack of hierarchy bears some limitations in the possibilities of searching and browsing. In this paper we investigate a new approach, based on the idea of integrating an ontology in the navigation interface of a folksonomy, and we describe an application that filters del.icio.us keywords through the WordNet hierarchy of concepts, to enrich the possibilities of navigation.Deriving a Large-Scale Taxonomy from Wikipedia.https://puma.uni-kassel.de/bibtex/25db72406c5681facd7ad47895937d86e/benzbenz2011-02-04T16:09:28+01:00download ol_web2.0 online ontology taxonomy wikipedia methods_concepthierarchy data_wikis <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Simone Paolo Ponzetto" itemprop="url" href="/author/Simone%20Paolo%20Ponzetto"><span itemprop="name">S. Ponzetto</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Michael Strube" itemprop="url" href="/author/Michael%20Strube"><span itemprop="name">M. Strube</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">AAAI</span>, </em></span><em>Seite <span itemprop="pagination">1440-1445</span>. </em><em><span itemprop="publisher">AAAI Press</span>, </em>(<em><span>2007<meta content="2007" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:28 CET 2011AAAIconf/aaai/20071440-1445Deriving a Large-Scale Taxonomy from Wikipedia.2007download ol_web2.0 online ontology taxonomy wikipedia methods_concepthierarchy data_wikis We take the category system inWikipedia as a conceptual network. We label the semantic relations between categories using methods based on connectivity in the network and lexicosyntactic matching. As a result we are able to derive a large scale taxonomy containing a large amount of subsumption, i.e. isa, relations. We evaluate the quality of the created resource by comparing it with ResearchCyc, one of the largest manually annotated ontologies, as well as computing semantic similarity between words in benchmarking datasets.dblpTowards automatic extraction of event and place semantics from flickr tagshttps://puma.uni-kassel.de/bibtex/2bf6f73d2ef74ca6f1d355fb5688b673c/benzbenz2011-02-04T16:09:28+01:00emerging event extraction flickr folksonomy geo learning ontology place semantic web ol_web2.0 methods_concepts <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tye Rattenbury" itemprop="url" href="/author/Tye%20Rattenbury"><span itemprop="name">T. Rattenbury</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Nathaniel Good" itemprop="url" href="/author/Nathaniel%20Good"><span itemprop="name">N. Good</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mor Naaman" itemprop="url" href="/author/Mor%20Naaman"><span itemprop="name">M. Naaman</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">SIGIR '07: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval</span>, </em></span><em>Seite <span itemprop="pagination">103--110</span>. </em><em>New York, NY, USA, </em><em><span itemprop="publisher">ACM Press</span>, </em>(<em><span>2007<meta content="2007" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:28 CET 2011New York, NY, USASIGIR '07: Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval103--110Towards automatic extraction of event and place semantics from flickr tags2007emerging event extraction flickr folksonomy geo learning ontology place semantic web ol_web2.0 methods_concepts We describe an approach for extracting semantics of tags, unstructured text-labels assigned to resources on the Web, based on each tag's usage patterns. In particular, we focus on the problem of extracting place and event semantics for tags that are assigned to photos on Flickr, a popular photo sharing website that supports time and location (latitude/longitude) metadata. We analyze two methods inspired by well-known burst-analysis techniques and one novel method: Scale-structure Identification. We evaluate the methods on a subset of Flickr data, and show that our Scale-structure Identification method outperforms the existing techniques. The approach and methods described in this work can be used in other domains such as geo-annotated web pages, where text terms can be extracted and associated with usage patterns.Semi-automatic extraction and modeling of ontologies using Wikipedia XML Corpushttps://puma.uni-kassel.de/bibtex/266bec053541e521fbe68c0119806ae49/benzbenz2011-02-04T16:09:28+01:00learning ol_web2.0 ontology ontology_learning semi_automatic wikipedia data_wikis <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="L. De Silva" itemprop="url" href="/author/L.%20De%20Silva"><span itemprop="name">L. Silva</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="L. Jayaratne" itemprop="url" href="/author/L.%20Jayaratne"><span itemprop="name">L. Jayaratne</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the</span>, </em></span><em>Seite <span itemprop="pagination">446-451</span>. </em>(<em><span>August 2009<meta content="August 2009" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:28 CET 2011Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on theAug.446-451Semi-automatic extraction and modeling of ontologies using Wikipedia XML Corpus2009learning ol_web2.0 ontology ontology_learning semi_automatic wikipedia data_wikis This paper introduces WikiOnto: a system that assists in the extraction and modeling of topic ontologies in a semi-automatic manner using a preprocessed document corpus derived from Wikipedia. Based on the Wikipedia XML Corpus, we present a three-tiered framework for extracting topic ontologies in quick time and a modeling environment to refine these ontologies. Using natural language processing (NLP) and other machine learning (ML) techniques along with a very rich document corpus, this system proposes a solution to a task that is generally considered extremely cumbersome. The initial results of the prototype suggest strong potential of the system to become highly successful in ontology extraction and modeling and also inspire further research on extracting ontologies from other semi-structured document corpora as well.Welcome to IEEE Xplore 2.0: Semi-automatic extraction and modeling of ontologies using Wikipedia XML CorpusThe Courseware Watchdog: an Ontology-based tool for finding and organizing learning materialhttps://puma.uni-kassel.de/bibtex/2850949481723b7dd03768ccd96b25cb9/benzbenz2011-02-04T16:09:27+01:00iccs_example learning ontology tool trias_example ol_web2.0 widely_related <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Julien Tane" itemprop="url" href="/author/Julien%20Tane"><span itemprop="name">J. Tane</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christoph Schmitz" itemprop="url" href="/author/Christoph%20Schmitz"><span itemprop="name">C. Schmitz</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerd Stumme" itemprop="url" href="/author/Gerd%20Stumme"><span itemprop="name">G. Stumme</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Steffen Staab" itemprop="url" href="/author/Steffen%20Staab"><span itemprop="name">S. Staab</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="R. Studer" itemprop="url" href="/author/R.%20Studer"><span itemprop="name">R. Studer</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Mobiles Lernen und Forschen - Beiträge der Fachtagung an der Universität</span>, </em></span><em>Seite <span itemprop="pagination">93-104</span>. </em><em><span itemprop="publisher">Kassel University Press</span>, </em>(<em><span>November 2003<meta content="November 2003" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:27 CET 2011Mobiles Lernen und Forschen - Beiträge der Fachtagung an der UniversitätNovember93-104The Courseware Watchdog: an Ontology-based tool for finding and organizing learning material2003iccs_example learning ontology tool trias_example ol_web2.0 widely_related Topics in education are changing with an ever faster pace. E-Learningresources tend to be more and more decentralised. Users need increasingly to be able touse the resources of the web. For this, they should have tools for finding and organizinginformation in a decentral way. In this, paper, we show how an ontology-based toolsuite allows to make the most of the resources available on the web.Ontology learning: state of the art and open issueshttps://puma.uni-kassel.de/bibtex/295b0f4f7c9c628e032d8bb4c69b432ed/benzbenz2011-02-04T16:09:27+01:00ol_web2.0 ontology ontology_learning semantic semanticweb toread toread_dbe overview <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Lina Zhou" itemprop="url" href="/author/Lina%20Zhou"><span itemprop="name">L. Zhou</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>Information Technology and Management</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">8 </span></span>(<span itemprop="issueNumber">3</span>):
<span itemprop="pagination">241--252</span></em> </span>(<em><span>2007<meta content="2007" itemprop="datePublished"/></span></em>)Fri Feb 04 16:09:27 CET 2011Information Technology and Management3241--252Ontology learning: state of the art and open issues82007ol_web2.0 ontology ontology_learning semantic semanticweb toread toread_dbe overview Abstract\ \ Ontology is one of the fundamental cornerstones of the semantic Web. The pervasive use of ontologies in information sharing and knowledge management calls for efficient and effective approaches to ontology development. Ontology learning, which seeks to discover ontological knowledge from various forms of data automatically or semi-automatically, can overcome the bottleneck of ontology acquisition in ontology development. Despite the significant progress in ontology learning research over the past decade, there remain a number of open problems in this field. This paper provides a comprehensive review and discussion of major issues, challenges, and opportunities in ontology learning. We propose a new learning-oriented model for ontology development and a framework for ontology learning. Moreover, we identify and discuss important dimensions for classifying ontology learning approaches and techniques. In light of the impact of domain on choosing ontology learning approaches, we summarize domain characteristics that can facilitate future ontology learning effort. The paper offers a road map and a variety of insights about this fast-growing field.Cross-lingual Information Retrieval with Explicit Semantic Analysishttps://puma.uni-kassel.de/bibtex/227c1c374a750725824118ac02ba5f2c6/hothohotho2011-01-17T12:48:19+01:00cross information lingual ol ontology <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Philipp Sorg" itemprop="url" href="/author/Philipp%20Sorg"><span itemprop="name">P. Sorg</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Philipp Cimiano" itemprop="url" href="/author/Philipp%20Cimiano"><span itemprop="name">P. Cimiano</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Working Notes for the CLEF 2008 Workshop</span>, </em></span>(<em><span>2008<meta content="2008" itemprop="datePublished"/></span></em>)Mon Jan 17 12:48:19 CET 2011Working Notes for the CLEF 2008 WorkshopCross-lingual Information Retrieval with Explicit Semantic AnalysisInproceedings2008cross information lingual ol ontology Multilingual Evidence Improves Clustering-based Taxonomy Extraction.https://puma.uni-kassel.de/bibtex/2813903a333a40ecf9a59ded552acb323/hothohotho2011-01-17T10:31:12+01:00antrag learning multilingual ol ontology <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hans Hjelm" itemprop="url" href="/author/Hans%20Hjelm"><span itemprop="name">H. Hjelm</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Paul Buitelaar" itemprop="url" href="/author/Paul%20Buitelaar"><span itemprop="name">P. Buitelaar</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">ECAI</span>, </em></span><em>Volume 178 von Frontiers in Artificial Intelligence and Applications, </em><em>Seite <span itemprop="pagination">288-292</span>. </em><em><span itemprop="publisher">IOS Press</span>, </em>(<em><span>2008<meta content="2008" itemprop="datePublished"/></span></em>)Mon Jan 17 10:31:12 CET 2011ECAIconf/ecai/2008288-292Frontiers in Artificial Intelligence and ApplicationsMultilingual Evidence Improves Clustering-based Taxonomy Extraction.1782008antrag learning multilingual ol ontology dblpOntology Learninghttps://puma.uni-kassel.de/bibtex/2f9f8bb0af1a8a514c270f83237313ac7/hothohotho2011-01-17T10:16:48+01:00learning ontology <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="P. Cimiano" itemprop="url" href="/author/P.%20Cimiano"><span itemprop="name">P. Cimiano</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="A. Mädche" itemprop="url" href="/author/A.%20M%c3%a4dche"><span itemprop="name">A. Mädche</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="S. Staab" itemprop="url" href="/author/S.%20Staab"><span itemprop="name">S. Staab</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="J. Völker" itemprop="url" href="/author/J.%20V%c3%b6lker"><span itemprop="name">J. Völker</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Handbook on Ontologies</span>, </em><em><span itemprop="publisher">Springer</span>, </em><em><span itemprop="bookEdition">2nd revised edition</span> Edition, </em></span>(<em><span>2009<meta content="2009" itemprop="datePublished"/></span></em>)Mon Jan 17 10:16:48 CET 2011Handbook on Ontologies2nd revised edition245--267International Handbooks on Information SystemsOntology Learning2009learning ontology Ontology learning techniques serve the purpose of supporting an ontology
engineer in the task of creating and maintaining an ontology. In this chapter, we present a comprehensive and concise introduction to the field of ontology learning.
We present a generic architecture for ontology learning systems and discuss its main components. In addition, we introduce the main problems and challenges addressed in the field and give an overview of the most important methods applied. We conclude with a brief discussion of advanced issues which pose interesting challenges to the state-of-the-art.DOI 10.1007/978-3-540-92673-3The Effectiveness of Latent Semantic Analysis for Building Up a Bottom-up Taxonomy from Folksonomy Tags.https://puma.uni-kassel.de/bibtex/2ec3c256e7d1f24cd9d407d3ce7e41d96/jaeschkejaeschke2010-09-16T19:52:06+02:00folksonomy lsa ontology tagging taxonomy <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Takeharu Eda" itemprop="url" href="/author/Takeharu%20Eda"><span itemprop="name">T. Eda</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Masatoshi Yoshikawa" itemprop="url" href="/author/Masatoshi%20Yoshikawa"><span itemprop="name">M. Yoshikawa</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Toshio Uchiyama" itemprop="url" href="/author/Toshio%20Uchiyama"><span itemprop="name">T. Uchiyama</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Tadasu Uchiyama" itemprop="url" href="/author/Tadasu%20Uchiyama"><span itemprop="name">T. Uchiyama</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>World Wide Web</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">12 </span></span>(<span itemprop="issueNumber">4</span>):
<span itemprop="pagination">421--440</span></em> </span>(<em><span>2009<meta content="2009" itemprop="datePublished"/></span></em>)Thu Sep 16 19:52:06 CEST 2010World Wide Web4421--440The Effectiveness of Latent Semantic Analysis for Building Up a Bottom-up Taxonomy from Folksonomy Tags.122009folksonomy lsa ontology tagging taxonomy In this paper, we evaluate the effectiveness of a semantic smoothing technique to organize folksonomy tags. Folksonomy tags have no explicit relations and vary because they form uncontrolled vocabulary. We discriminates so-called subjective tags like “cool” and “fun” from folksonomy tags without any extra knowledge other than folksonomy triples and use the level of tag generalization to form the objective tags into a hierarchy. We verify that entropy of folksonomy tags is an effective measure for discriminating subjective folksonomy tags. Our hierarchical tag allocation method guarantees the number of children nodes and increases the number of available paths to a target node compared to an existing tree allocation method for folksonomy tags.The state of the art in tag ontologies: a semantic model for tagging and folksonomieshttps://puma.uni-kassel.de/bibtex/2cb56167e7e5e0dbfee017671064ff81e/jaeschkejaeschke2010-08-12T09:24:32+02:00folksonomy ontology semantic tagging web <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hak Lae Kim" itemprop="url" href="/author/Hak%20Lae%20Kim"><span itemprop="name">H. Kim</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Simon Scerri" itemprop="url" href="/author/Simon%20Scerri"><span itemprop="name">S. Scerri</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="John G. Breslin" itemprop="url" href="/author/John%20G.%20Breslin"><span itemprop="name">J. Breslin</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Stefan Decker" itemprop="url" href="/author/Stefan%20Decker"><span itemprop="name">S. Decker</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Hong Gee Kim" itemprop="url" href="/author/Hong%20Gee%20Kim"><span itemprop="name">H. Kim</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">DCMI '08: Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications</span>, </em></span><em>Seite <span itemprop="pagination">128--137</span>. </em><em><span itemprop="publisher">Dublin Core Metadata Initiative</span>, </em>(<em><span>2008<meta content="2008" itemprop="datePublished"/></span></em>)Thu Aug 12 09:24:32 CEST 2010DCMI '08: Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications128--137The state of the art in tag ontologies: a semantic model for tagging and folksonomies2008folksonomy ontology semantic tagging web There is a growing interest into how we represent and share tagging data in collaborative tagging systems. Conventional tags, meaning freely created tags that are not associated with a structured ontology, are not naturally suited for collaborative processes, due to linguistic and grammatical variations, as well as human typing errors. Additionally, tags reflect personal views of the world by individual users, and are not normalised for synonymy, morphology or any other mapping. Our view is that the conventional approach provides very limited semantic value for collaboration. Moreover, in cases where there is some semantic value, automatically sharing semantics via computer manipulations is extremely problematic. This paper explores these problems by discussing approaches for collaborative tagging activities at a semantic level, and presenting conceptual models for collaborative tagging activities and folksonomies. We present criteria for the comparison of existing tag ontologies and discuss their strengths and weaknesses in relation to these criteria.From folksonomies to ontologies: employing wisdom of the crowds to serve learning purposeshttps://puma.uni-kassel.de/bibtex/2dd5cdcc6449d97622033bbebcd4d1874/jaeschkejaeschke2010-08-09T16:07:33+02:00folksonomy learning ol_tut2010 ontology tagging <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Mathias Lux" itemprop="url" href="/author/Mathias%20Lux"><span itemprop="name">M. Lux</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gisela Dösinger" itemprop="url" href="/author/Gisela%20D%c3%b6singer"><span itemprop="name">G. Dösinger</span></a></span>. </span><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><span itemtype="http://schema.org/Periodical" itemscope="itemscope" itemprop="isPartOf"><span itemprop="name"><em>International Journal of Knowledge and Learning</em></span></span> <em><span itemtype="http://schema.org/PublicationVolume" itemscope="itemscope" itemprop="isPartOf"><span itemprop="volumeNumber">3 </span></span>(<span itemprop="issueNumber">4-5</span>):
<span itemprop="pagination">515--528</span></em> </span>(<em><span>Januar 2008<meta content="Januar 2008" itemprop="datePublished"/></span></em>)Mon Aug 09 16:07:33 CEST 2010International Journal of Knowledge and Learningjan4-5515--528From folksonomies to ontologies: employing wisdom of the crowds to serve learning purposes32008folksonomy learning ol_tut2010 ontology tagging Is Web 2.0 just hype or just a buzzword, which might disappear in the near future One way to find answers to these questions is to investigate the actual benefit of the Web 2.0 for real use cases. Within this contribution we study a very special aspect of the Web 2.0 the folksonomy and its use within self-directed learning. Guided by conceptual principles of emergent computing we point out methods, which might be able to let semantics emerge from folksonomies and discuss the effect of the results in self-directed learning.Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledgehttps://puma.uni-kassel.de/bibtex/2ba43b0db4b8f7cb091fd55d59e170477/hothohotho2010-06-17T20:42:17+02:002010 myown ol ontology semantics websci websci10 <span class="authorEditorList"><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Dominik Benz" itemprop="url" href="/author/Dominik%20Benz"><span itemprop="name">D. Benz</span></a></span>, <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Andreas Hotho" itemprop="url" href="/author/Andreas%20Hotho"><span itemprop="name">A. Hotho</span></a></span>, und <span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Gerd Stumme" itemprop="url" href="/author/Gerd%20Stumme"><span itemprop="name">G. Stumme</span></a></span>. </span><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 2nd Web Science Conference (WebSci10)</span>, </em></span><em>Raleigh, NC, USA, </em>(<em><span>2010<meta content="2010" itemprop="datePublished"/></span></em>)Thu Jun 17 20:42:17 CEST 2010Raleigh, NC, USAProceedings of the 2nd Web Science Conference (WebSci10)Semantics made by you and me: Self-emerging ontologies can capture the diversity of shared knowledge20102010 myown ol ontology semantics websci websci10