TY - CONF AU - Benz, Dominik AU - Grobelnik, Marko AU - Hotho, Andreas AU - Jäschke, Robert AU - Mladenic, Dunja AU - Servedio, Vito D. P. AU - Sizov, Sergej AU - Szomszor, Martin A2 - Alani, Harith A2 - Staab, Steffen A2 - Stumme, Gerd T1 - Analyzing Tag Semantics Across Collaborative Tagging Systems T2 - Proceedings of the Dagstuhl Seminar on Social Web Communities PB - C1 - PY - 2008/ CY - VL - IS - 08391 SP - EP - UR - http://www.kde.cs.uni-kassel.de/pub/pdf/benz2008analyzing.pdf DO - KW - 2008 KW - ol_web2.0 KW - itegpub KW - iin2009 KW - tagorapub KW - widely_related KW - myown KW - tag_semantics KW - dagstuhl L1 - SN - N1 - N1 - AB - The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance. ER - TY - CONF AU - Benz, Dominik AU - Grobelnik, Marko AU - Hotho, Andreas AU - Jäschke, Robert AU - Mladenic, Dunja AU - Servedio, Vito D. P. AU - Sizov, Sergej AU - Szomszor, Martin A2 - Alani, Harith A2 - Staab, Steffen A2 - Stumme, Gerd T1 - Analyzing Tag Semantics Across Collaborative Tagging Systems T2 - Proceedings of the Dagstuhl Seminar on Social Web Communities PB - C1 - PY - 2008/ CY - VL - IS - 08391 SP - EP - UR - http://www.kde.cs.uni-kassel.de/pub/pdf/benz2008analyzing.pdf DO - KW - 2008 KW - ol_web2.0 KW - itegpub KW - iin2009 KW - tagorapub KW - widely_related KW - myown KW - tag_semantics KW - dagstuhl L1 - SN - N1 - N1 - AB - The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance. ER - TY - CONF AU - Benz, Dominik AU - Grobelnik, Marko AU - Hotho, Andreas AU - Jäschke, Robert AU - Mladenic, Dunja AU - Servedio, Vito D. P. AU - Sizov, Sergej AU - Szomszor, Martin A2 - Alani, Harith A2 - Staab, Steffen A2 - Stumme, Gerd T1 - Analyzing Tag Semantics Across Collaborative Tagging Systems T2 - Social Web Communities PB - Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik C1 - Dagstuhl, Germany PY - 2008/ CY - VL - IS - 08391 SP - EP - UR - http://drops.dagstuhl.de/opus/volltexte/2008/1785 DO - KW - 2008 KW - tagging KW - taggingsurvey KW - collaborative KW - semantic KW - myown KW - dagstuhl KW - web L1 - SN - N1 - N1 - AB - The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance. ER - TY - CONF AU - Benz, Dominik AU - Grobelnik, Marko AU - Hotho, Andreas AU - Jäschke, Robert AU - Mladenic, Dunja AU - Servedio, Vito D. P. AU - Sizov, Sergej AU - Szomszor, Martin A2 - Alani, Harith A2 - Staab, Steffen A2 - Stumme, Gerd T1 - Analyzing Tag Semantics Across Collaborative Tagging Systems T2 - Social Web Communities PB - Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik C1 - Dagstuhl, Germany PY - 2008/10 CY - VL - IS - 08391 SP - EP - UR - http://drops.dagstuhl.de/opus/volltexte/2008/1785 DO - KW - 2008 KW - tagging KW - collaborative KW - semantic KW - social KW - myown KW - dagstuhl KW - web L1 - SN - N1 - N1 - AB - The objective of our group was to exploit state-of-the-art Information Retrieval methods for finding associations and dependencies between tags, capturing and representing differences in tagging behavior and vocabulary of various folksonomies, with the overall aim to better understand the semantics of tags and the tagging process. Therefore we analyze the semantic content of tags in the Flickr and Delicious folksonomies. We find that: tag context similarity leads to meaningful results in Flickr, despite its narrow folksonomy character; the comparison of tags across Flickr and Delicious shows little semantic overlap, being tags in Flickr associated more to visual aspects rather than technological as it seems to be in Delicious; there are regions in the tag-tag space, provided with the cosine similarity metric, that are characterized by high density; the order of tags inside a post has a semantic relevance. ER - TY - JOUR AU - Fortuna, Blaz AU - Grobelnik, Marko AU - Mladenić, Dunja T1 - Semi-automatic data-driven ontology construction system JO - PY - 2006/ VL - IS - SP - EP - UR - DO - KW - text KW - ol L1 - SN - N1 - N1 - AB - In this paper we present a new version of OntoGen system for semi-automatic data-driven ontology construction. The system is based on a novel ontology learning framework which formalizes and extends the role of machine learning and text mining algorithms used in the previous version. List of new features includes extended number of supported ontology formats (RDFS and OWL), supervised methods for concept discovery (based on Active Learning), adding of new instances to ontology and improved user interface (based on comments from the users). ER - TY - GEN AU - Grobelnik, Marko AU - Mladenić, Dunja A2 - T1 - Knowledge Discovery for Ontology Construction JO - PB - John Wiley & Sons, Ltd C1 - PY - 2006/ VL - IS - SP - 9 EP - 27 UR - http://dx.doi.org/10.1002/047003033X.ch2 DO - 10.1002/047003033X.ch2 KW - ol_web2.0 KW - ontology_learning KW - knowledge_discovery L1 - N1 - Knowledge Discovery for Ontology Construction - Semantic Web Technologies: Trends and Research in Ontology-based Systems - Grobelnik - Wiley Online Library N1 - AB - Summary 10.1002/047003033X.ch2.abs This chapter contains sections titled: * Introduction * Knowledge Discovery * Ontology Definition * Methodology for Semi-automatic Ontology Construction * Ontology Learning Scenarios * Using Knowledge Discovery for Ontology Learning * Related Work on Ontology Construction * Discussion and Conclusion * Acknowledgments * References ER - TY - CONF AU - Brank, Janez AU - Grobelnik, Marko AU - Mladenić, Dunja A2 - T1 - A Survey of Ontology Evaluation Techniques T2 - Proc. of 8th Int. multi-conf. Information Society PB - C1 - PY - 2005/ CY - VL - IS - SP - 166 EP - 169 UR - DO - KW - ol_web2.0 KW - widely_related KW - ontology_learning KW - evaluation L1 - SN - N1 - A nice survey of ontology evaluation methods, easy to read. N1 - AB - An ontology is an explicit formal conceptualization of some domain of interest. Ontologies are increasingly used in various fields such as knowledge management, information extraction, and the semantic web. Ontology evaluation is the problem of assessing a given ontology from the point of view of a particular criterion of application, typically in order to determine which of several ontologies would best suit a particular purpose. This paper presents a survey of the state of the art in ontology evaluation. ER - TY - CONF AU - Brank, Janez AU - Grobelnik, Marko AU - Mladenić, Dunja A2 - T1 - A Survey of Ontology Evaluation Techniques T2 - Proc. of 8th Int. multi-conf. Information Society PB - C1 - PY - 2005/ CY - VL - IS - SP - 166 EP - 169 UR - DO - KW - ol KW - survey KW - evaluation KW - ontology L1 - SN - N1 - A nice survey of ontology evaluation methods, easy to read. N1 - AB - ER - TY - CONF AU - Berendt, Bettina AU - Hotho, Andreas AU - Mladenic, Dunja AU - van Someren, Maarten AU - Spiliopoulou, Myra AU - Stumme, Gerd A2 - Berendt, Bettina A2 - Hotho, Andreas A2 - Mladenic, Dunja A2 - van Someren, Maarten A2 - Spiliopoulou, Myra A2 - Stumme, Gerd T1 - A Roadmap for Web Mining: From Web to Semantic Web. T2 - Web Mining: From Web to Semantic Web PB - Springer C1 - Heidelberg PY - 2004/ CY - VL - 3209 IS - SP - 1 EP - 22 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt2004roadmap.pdf DO - KW - pkdd KW - workshop KW - itegpub KW - 2004 KW - proceedings KW - semantic KW - l3s KW - ecml KW - myown KW - roadmap KW - ewmf KW - mining KW - web L1 - SN - N1 - N1 - AB - The purpose of Web mining is to develop methods and systems for discovering models of objects and processes on the World Wide Web and for web-based systems that show adaptive performance. Web Mining integrates three parent areas: Data Mining (we use this term here also for the closely related areas of Machine Learning and Knowledge Discovery), Internet technology and World Wide Web, and for the more recent Semantic Web. The World Wide Web has made an enormous amount of information electronically accessible. The use of email, news and markup languages like HTML allow users to publish and read documents at a world-wide scale and to communicate via chat connections, including information in the form of images and voice records. The HTTP protocol that enables access to documents over the network via Web browsers created an immense improvement in communication and access to information. For some years these possibilities were used mostly in the scientific world but recent years have seen an immense growth in popularity, supported by the wide availability of computers and broadband communication. The use of the internet for other tasks than finding information and direct communication is increasing, as can be seen from the interest in ldquoe-activitiesrdquo such as e-commerce, e-learning, e-government, e-science. ER - TY - CONF AU - Berendt, Bettina AU - Hotho, Andreas AU - Mladenic, Dunja AU - van Someren, Maarten AU - Spiliopoulou, Myra AU - Stumme, Gerd A2 - Berendt, Bettina A2 - Hotho, Andreas A2 - Mladenic, Dunja A2 - van Someren, Maarten A2 - Spiliopoulou, Myra A2 - Stumme, Gerd T1 - A Roadmap for Web Mining: From Web to Semantic Web. T2 - Web Mining: From Web to Semantic Web PB - Springer C1 - Heidelberg PY - 2004/ CY - VL - 3209 IS - SP - 1 EP - 22 UR - http://www.kde.cs.uni-kassel.de/stumme/papers/2004/berendt2004roadmap.pdf DO - KW - pkdd KW - workshop KW - itegpub KW - 2004 KW - proceedings KW - semantic KW - l3s KW - ecml KW - myown KW - roadmap KW - ewmf KW - mining KW - web L1 - SN - N1 - Publications of Gerd Stumme N1 - AB - The purpose of Web mining is to develop methods and systems for discovering models of objects and processes on the World Wide Web and for web-based systems that show adaptive performance. Web Mining integrates three parent areas: Data Mining (we use this term here also for the closely related areas of Machine Learning and Knowledge Discovery), Internet technology and World Wide Web, and for the more recent Semantic Web. The World Wide Web has made an enormous amount of information electronically accessible. The use of email, news and markup languages like HTML allow users to publish and read documents at a world-wide scale and to communicate via chat connections, including information in the form of images and voice records. The HTTP protocol that enables access to documents over the network via Web browsers created an immense improvement in communication and access to information. For some years these possibilities were used mostly in the scientific world but recent years have seen an immense growth in popularity, supported by the wide availability of computers and broadband communication. The use of the internet for other tasks than finding information and direct communication is increasing, as can be seen from the interest in ldquoe-activitiesrdquo such as e-commerce, e-learning, e-government, e-science. ER -