Mon, 21 Jul 2008 00:23:41 BST CiteULike: Group: Adaptive-Web - with tag dlpaws http://www.citeulike.org/group/2118/tag/dlpaws CiteULike.org en-gb Copyright © 2004-2008 citeulike.org http://www.citeulike.org/group/2118/article/2682613 <i>(2007), pp. 417-418.</i> Recommending related papers based on digital library access records Stefan Pohl Filip Radlinski Thorsten Joachims doi:10.1145/1255175.1255260 (2007), pp. 417-418. 2008-04-17T15:53:00-00:00 2007 417 418 ACM academic-reference collaborative-filtering dlpaws log-mining http://www.citeulike.org/group/2118/article/1445552 <i>User Modeling and User-Adapted Interaction, Vol. 17, No. 3. (July 2007), pp. 217-255.</i> A content-collaborative recommender that exploits WordNet-based user profiles for neighborhood formation Degemmis Marco Lops Pasquale Semeraro Giovanni doi:10.1007/s11257-006-9023-4 User Modeling and User-Adapted Interaction, Vol. 17, No. 3. (July 2007), pp. 217-255. 2007-07-10T06:33:10-00:00 2007 User Modeling and User-Adapted Interaction 0924-1868 17 3 217 255 Springer collaborative-filtering concept-extraction concept-map dlpaws japaws jlpaws pbblog recommender http://www.citeulike.org/group/2118/article/848978 <i>Intelligent Systems, IEEE [see also IEEE Intelligent Systems and Their Applications], Vol. 18, No. 1. (2003), pp. 14-21.</i><br /><br />To bring the Semantic Web to life and provide advanced knowledge services, we need efficient ways to access and extract knowledge from Web documents. Although Web page annotations could facilitate such knowledge gathering, annotations are rare and will probably never be rich or detailed enough to cover all the knowledge these documents contain. Manual annotation is impractical and unscalable, and automatic annotation tools remain largely undeveloped. Specialized knowledge services therefore require tools that can search and extract specific knowledge directly from unstructured text on the Web, guided by an ontology that details what type of knowledge to harvest. An ontology uses concepts and relations to classify domain knowledge. Other researchers have used ontologies to support knowledge extraction, but few have explored their full potential in this domain. The paper considers the Artequakt project which links a knowledge extraction tool with an ontology to achieve continuous knowledge support and guide information extraction. The extraction tool searches online documents and extracts knowledge that matches the given classification structure. It provides this knowledge in a machine-readable format that will be automatically maintained in a knowledge base (KB). Knowledge extraction is further enhanced using a lexicon-based term expansion mechanism that provides extended ontology terminology. Automatic ontology-based knowledge extraction from Web documents H Alani Sanghee Kim DE Millard MJ Weal W Hall PH Lewis NR Shadbolt Intelligent Systems, IEEE [see also IEEE Intelligent Systems and Their Applications], Vol. 18, No. 1. (2003), pp. 14-21. 2006-09-18T14:47:09-00:00 2003 Intelligent Systems, IEEE [see also IEEE Intelligent Systems and Their Applications] 18 1 14 21 concept-extraction dlpaws ontology sspaws