BibliographyType,ISBN,Identifier,Author,Title,Journal,Volume,Number,Month,Pages,Year,Address,Note,URL,Booktitle,Chapter,Edition,Series,Editor,Publisher,ReportType,Howpublished,Institution,Organizations,School,Annote,Custom1,Custom2,Custom3,Custom4,Custom5
10,"","cattuto-2008","Cattuto, Ciro; Benz, Dominik; Hotho, Andreas & Stumme, Gerd","Semantic Analysis of Tag Similarity Measures in Collaborative Tagging Systems","",,,"","",2008,"","","http://www.citebase.org/abstract?id=oai:arXiv.org:0805.2045","","","","","","","","","","","",""," Social bookmarking systems allow users to organise collections of resources on the Web in a collaborative fashion. The increasing popularity of these systems as well as first insights into their emergent semantics have made them relevant to disciplines like knowledge extraction and ontology learning. The problem of devising methods to measure the semantic relatedness between tags and characterizing it semantically is still largely open. Here we analyze three measures of tag relatedness: tag co-occurrence, cosine similarity of co-occurrence distributions, and FolkRank, an adaptation of the PageRank algorithm to folksonomies. Each measure is computed on tags from a large-scale dataset crawled from the social bookmarking system del.icio.us. To provide a semantic grounding of our findings, a connection to WordNet (a semantic lexicon for the English language) is established by mapping tags into synonym sets of WordNet, and applying there well-known metrics of semantic similarity. Our results clearly expose different characteristics of the selected measures of relatedness, making them applicable to different subtasks of knowledge extraction such as synonym detection or discovery of concept hierarchies.","","2008 analysis learning myown ol ontology semantic similarity tag ","",""
7,"","heylighen98bootstrapping","Heylighen, Francis","Bootstrapping knowledge representations: from entailment meshes via semantic nets to learning webs","Kybernetes",30,5/6,"","691--722",2001,"","","citeseer.nj.nec.com/francis96bootstrapping.html","","","","","","","","","","","","","","meh: general ontology, knowledge structures","folksonomy kdubiq learning ontology semantic summerschool ","",""
6,"3-540-34544-2","hoser2006semantic","Hoser, Bettina; Hotho, Andreas; Jäschke, Robert; Schmitz, Christoph & Stumme, Gerd","Semantic Network Analysis of Ontologies","",4011,,"June","514-529",2006,"Budva, Montenegro","","http://www.kde.cs.uni-kassel.de/hotho/pub/2006/hoser_sna_eswc2005.pdf","Proceedings of the 3rd European Semantic Web Conference","","","LNCS","","Springer","","","","","","","","","2006 analysis myown network ontology semantic sna social web ","",""
7,"","McRae:2005:Behav-Res-Methods:16629288","McRae, K; Cree, G S; Seidenberg, M S & McNorgan, C","Semantic feature production norms for a large set of living and nonliving things","Behav Res Methods",37,4,"Nov","547-559",2005,"","","http://www.ncbi.nlm.nih.gov/pubmed/16629288","","","","","","","","","","","","","Semantic features have provided insight into numerous behavioral phenomena concerning concepts, categorization, and semantic memory in adults, children, and neuropsychological populations. Numerous theories and models in these areas are based on representations and computations involving semantic features. Consequently, empirically derived semantic feature production norms have played, and continue to play, a highly useful role in these domains. This article describes a set of feature norms collected from approximately 725 participants for 541 living (dog) and nonliving (chair) basic-level concepts, the largest such set of norms developed to date. This article describes the norms and numerous statistics associated with them. Our aim is to make these norms available to facilitate other research, while obviating the need to repeat the labor-intensive methods involved in collecting and analyzing such norms. The full set of norms may be downloaded from www.psychonomic.org/archive.","","dataset grounding ol ontology relation semantic toread ","",""
5,"3-540-29324-8","schmitz2006kollaboratives","Schmitz, Christoph; Hotho, Andreas; Jäschke, Robert & Stumme, Gerd","Kollaboratives Wissensmanagement","",,,"","273-290",2006,"","","http://www.semantic-web.at/springer/abstracts/3d_Schmitz_KollabWM.pdf","Semantic Web - Wege zur vernetzten Wissensgesellschaft","","","","Pellegrini, Tassilo & Blumauer, Andreas","Springer","","","","","","","Wissensmanagement in zentralisierten Wissensbasen erfordert einen hohen Aufwand für Erstellung und Wartung, und es entspricht nicht immer den Anforderungen der Benutzer. Wir geben in diesem Kapitel einen Überblick über zwei aktuelle Ansätze, die durch kollaboratives Wissensmanagement diese Probleme lösen können. Im Peer-to-Peer-Wissensmanagement unterhalten Benutzer dezentrale Wissensbasen, die dann vernetzt werden können, um andere Benutzer eigene Inhalte nutzen zu lassen. Folksonomies versprechen, die Wissensakquisition so einfach wie möglich zu gestalten und so viele Benutzer in den Aufbau und die Pflege einer gemeinsamen Wissensbasis einzubeziehen.","","2006 Wissensmanagement collaborative folksonomy knowledge management myown semantic web ","",""
6,"978-3-540-34415-5","schmitz2006mining","Schmitz, Christoph; Hotho, Andreas; Jäschke, Robert & Stumme, Gerd","Mining Association Rules in Folksonomies","",,,"July","261-270",2006,"Ljubljana","","http://www.kde.cs.uni-kassel.de/hotho/pub/2006/schmitz2006asso_ifcs.pdf","Data Science and Classification (Proc. IFCS 2006 Conference)","","","Studies in Classification, Data Analysis, and Knowledge Organization","Batagelj, V.; Bock, H.-H.; Ferligoj, A. & Žiberna, A.","Springer","","","","","","","","","2006 analysis association folksonomy kdubiq myown network rules semantic seminar2006 sosbuch summerschool ","",""
1,"","keyhere","Staab, Steffen & Studer, Rudi","Handbook on ontologies","",,,"","--",2004,"Berlin; New York","","","International handbooks on information systems","","","","","Springer","","","","","","","","","handbook ontology semantic survey web ","",""
3,"","msw2004","","International Workshop on Mining for and from the Semantic Web (MSW2004)","",,,"AUG","",2004,"","located at the 10th International ACM SIGKDD Conference on Knowledge Discovery and Data Mining KDD 2004, 22nd August 2004, Seattle, WA, USA","http://www.kde.cs.uni-kassel.de/hotho/pub/2004/msw2004_proceedings.pdf","","","","","Hotho, Andreas; Sure, York & Getoor, Lise","","","","","","","","","","2004 mining myown semantic web workshop ","",""
3,"3-540-41066-X","WS_BHS02","","Semantic Web Mining","",,,"August 20","",2002,"Helsinki","","","Proc. of the Semantic Web Mining Workshop","","","","Berendt, B.; Hotho, A. & Stumme, G.","Workshop at 13th Europ. Conf. on Machine Learning (ECML'02) / 6th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'02)","","","","","","","","","2002 mining myown semantic web ","",""
3,"","stumme_semwebmine_ws01","","Semantic Web Mining","",,,"September 3rd","",2001,"Freiburg","","","Proc. of the Semantic Web Mining Workshop","","","","Stumme, G.; Hotho, A. & Berendt, B.","Workshop at 12th Europ. Conf. on Machine Learning (ECML'01) / 5th Europ. Conf. on Principles and Practice of Knowledge Discovery in Databases (PKDD'01)","","","","","","","","","2001 mining myown semantic web ","",""