BibSonomyburst/user/eswc2008/searchBibSonomy RSS feed for /user/eswc2008/search2012-02-16T11:47:14+01:00http://www.bibsonomy.org/bibtex/24351fdf2185be4ce88dae92d12848dae/eswc2008eswc20082008-05-28T14:50:06+02:00datasets provenance search sitemaps crawling foundational-issues-storage-and-retrieval <span class="authorEditorList"><a href="/author/Cyganiak">Richard Cyganiak</a>, <a href="/author/Delbru">Renaud Delbru</a>, <a href="/author/Stenzhorn">Holger Stenzhorn</a>, <a href="/author/Tummarello">Giovanni Tummarello</a>, and <a href="/author/Decker">Stefan Decker</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:50:06 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSExposing Large Datasets with Semantic Sitemaps2008datasets provenance search sitemaps crawling foundational-issues-storage-and-retrieval Increasing amounts of RDF data are available on the Web for consumption by Semantic Web browsers and indexing by Semantic Web search engines. Current Semantic Web publishing practices, however, do not directly support efficient discovery and high-performance retrieval by clients and search engines. We propose an extension to the Sitemaps protocol which provides a simple and effective solution: Data publishers create Semantic Sitemaps to announce and describe their data so that clients can choose the most appropriate access method. We show how this protocol enables an extended notion of authoritative information across different access methods.http://www.bibsonomy.org/bibtex/2e89c1407d23363623b309b221e2ca1e9/eswc2008eswc20082008-05-28T14:50:00+02:00document semantic search spreading desktop activation retrieval <span class="authorEditorList"><a href="/author/Schumacher">Kinga Schumacher</a>, <a href="/author/Sintek">Michael Sintek</a>, and <a href="/author/Sauermann">Leo Sauermann</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:50:00 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSCombining Meta Data and Document Search with Spreading Activation for Semantic Desktop Search2008document semantic search spreading desktop activation retrieval The Semantic Desktop is a means to support users in Personal Information Management (PIM). It provides an excellent test bed for Semantic Web technology: resources (e. g., persons, projects, messages, documents) are distributed amongst multiple systems, ontologies are used to link and annotate them. Finding information is a core element in PIM. For the end user, the search interface has to be intuitive to use, natural language queries provide a simple mean to express requests. State of the art semantic search engines focus on metadata search or on semantic document retrieval. We combine both approaches to search the Semantic Desktop exploiting all available information, where we build on semantic teleporting and spreading activation. This combination is able to answer queries with instances, subgraphs of the knowledge base, and with relevant documents. We evaluated our approach on ESWC 2007 data in comparison with Google site search.http://www.bibsonomy.org/bibtex/21adb4b2e579baebf8472f1ab8160098e/eswc2008eswc20082008-05-28T14:49:56+02:00web semantic search <span class="authorEditorList"><a href="/author/Bhagdev">Ravish Bhagdev</a>, <a href="/author/Chapman">Sam Chapman</a>, <a href="/author/Ciravegna">Fabio Ciravegna</a>, <a href="/author/Lanfranchi">Vitaveska Lanfranchi</a>, and <a href="/author/Petrelli">Daniela Petrelli</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:49:56 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSHybrid Search: Effectively Combining Keywords and Ontology-based Searches2008web semantic search This paper describes hybrid search, a semantic methodology supporting both document and knowledge retrieval via the flexible combination of ontology-based search and keyword-matching. Hybrid search aims to smoothly cope with lack of semantic coverage of document content, which is one of the main limitations of current semantic search methods. In this paper we define hybrid search formally, discuss its compatibility with the current semantic trends and present a reference implementation: K-Search. We then show how the methodology outperforms both keyword-based search and pure semantic search in terms of precision and recall in a set of experiments performed on a very large collection of documents. Experiments carried out with professional users show that users understand the paradigm and consider it very powerful and reliable. K-Search has been ported to 2 applications released at Rolls-Royce plc for searching technical documentation about jet engines.http://www.bibsonomy.org/bibtex/232a549f40bd649acda1998c996cb5a1d/eswc2008eswc20082008-05-28T14:49:54+02:00top-k clustered-graph ranking q2semantic queries scalability structure query search <span class="authorEditorList"><a href="/author/Wang">Haofen Wang</a>, <a href="/author/Zhang">Kang Zhang</a>, <a href="/author/Liu">Qiaoling Liu</a>, <a href="/author/Tran">Duc Thanh Tran</a>, and <a href="/author/Yu">Yong Yu</a> </span><em>Proceedings of the 5th European Semantic Web Conference, </em><em>Berlin, Heidelberg, </em><em>Springer Verlag, </em>(<em>June 2008</em>)Wed May 28 14:49:54 CEST 2008Berlin, HeidelbergProceedings of the 5th European Semantic Web ConferenceJuneLNCSQ2Semantic: A Lightweight Keyword Interface to Semantic Search2008top-k clustered-graph ranking q2semantic queries scalability structure query search The increasing amount of data on the Semantic Web offers opportunities for semantic search. However, formal query hinders the casual users in expressing their information need as they might be not familiar with the query's syntax or the underlying ontology. Because keyword interfaces are easier to handle for casual users, many approaches aim to translate keywords to formal queries. However, these approaches yet feature only very basic query ranking and do not scale to large repositories. We tackle the scalability problem by proposing a novel clustered-graph structure that corresponds to only a summary of the original ontology. The so reduced data space is then used in the exploration for the computation of top-k queries. Additionally, we adopt several mechanisms for query ranking, which can consider many factors such as the query length and the relevance of ontology elements w.r.t. the query. Our experimental results performed against our implemented system Q2Semantic show that we achieve good performance on many datasets of different sizes.