@inproceedings{conf/semweb/GaroufiZG08,
	title = {Graph-Theoretic Analysis of Collaborative Knowledge Bases in Natural Language Processing.},
	author = {Konstantina Garoufi and Torsten Zesch and Iryna Gurevych},
	booktitle = {International Semantic Web Conference (Posters & Demos)},
	crossref = {conf/semweb/2008p},
	editor = {Christian Bizer and Anupam Joshi},
	publisher = {CEUR-WS.org},
	series = {CEUR Workshop Proceedings},
	url = {http://dblp.uni-trier.de/db/conf/semweb/iswc2008p.html#GaroufiZG08},
	volume = {401},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/24d273d5959cf1e296d27bbc174f79117/dblp},
	description = {dblp},
	date = {2008-10-29}, ee = {http://ceur-ws.org/Vol-401/iswc2008pd_submission_35.pdf},
	keywords = {dblp }
}

@inproceedings{conf/semco/HartmannZMG08,
	title = {Using Similarity Measures for Context-Aware User Interfaces.},
	author = {Melanie Hartmann and Torsten Zesch and Max Mühlhäuser and Iryna Gurevych},
	booktitle = {ICSC},
	crossref = {conf/semco/2008},
	pages = {190-197},
	publisher = {IEEE Computer Society},
	url = {http://dblp.uni-trier.de/db/conf/semco/icsc2008.html#HartmannZMG08},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/24c195d9442935c07718884e0eb97acb5/dblp},
	description = {dblp},
	ee = {http://doi.ieeecomputersociety.org/10.1109/ICSC.2008.94}, date = {2008-09-21},
	keywords = {dblp }
}

@inproceedings{conf/aaai/ZeschMG08,
	title = {Using Wiktionary for Computing Semantic Relatedness.},
	author = {Torsten Zesch and Christof Müller and Iryna Gurevych},
	booktitle = {AAAI},
	crossref = {conf/aaai/2008},
	editor = {Dieter Fox and Carla P. Gomes},
	pages = {861-866},
	publisher = {AAAI Press},
	url = {http://dblp.uni-trier.de/db/conf/aaai/aaai2008.html#ZeschMG08},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/2814bd9b56b4dc79173ed3785bd0c42a5/dblp},
	description = {dblp},
	isbn = {978-1-57735-368-3}, date = {2008-08-15},
	keywords = {dblp }
}

@inproceedings{conf/acl/GurevychMZ07,
	title = {What to be? - Electronic Career Guidance Based on Semantic Relatedness.},
	author = {Iryna Gurevych and Christof Müller and Torsten Zesch},
	booktitle = {ACL},
	crossref = {conf/acl/2007},
	publisher = {The Association for Computer Linguistics},
	url = {http://dblp.uni-trier.de/db/conf/acl/acl2007.html#GurevychMZ07},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2bf01c968b8578528ac0b33eae12637b9/dblp},
	description = {dblp},
	ee = {http://aclweb.org/anthology-new/P/P07/P07-1130.pdf}, date = {2008-07-03},
	keywords = {dblp }
}

@inproceedings{zesch2006acd,
	title = {Automatically creating datasets for measures of semantic relatedness},
	address = {Sydney, Australia},
	author = {Torsten Zesch and Iryna Gurevych},
	booktitle = {COLING/ACL 2006 Workshop on Linguistic Distances},
	pages = {16--24},
	url = {http://www.ukp.tu-darmstadt.de/sites/www.ukp.tu-darmstadt.de/files/datasets.zip},
	year = {2006},
	biburl = {http://www.bibsonomy.org/bibtex/27f05ca2dd5d49dd268a82eb1800ad01d/brightbyte},
	description = {stuff from citeyoulike},
	priority = {2}, citeulike-article-id = {2354965},
	keywords = {relatedness semantic }
}

@inproceedings{ZeschMuellerGurevych2008,
	title = {{Extracting Lexical Semantic Knowledge from Wikipedia and Wiktionary}},
	author = {Torsten Zesch and Christof M{\"u}ller and Iryna Gurevych},
	booktitle = {Proceedings of the Conference on Language Resources and Evaluation (LREC)},
	url = {http://elara.tk.informatik.tu-darmstadt.de/publications/2008/lrec08_camera_ready.pdf},
	year = {2008},
	biburl = {http://www.bibsonomy.org/bibtex/2535de02686dbbd8de52571e4019ef4c9/hkorte},
	description = {JWPL},
	keywords = {lexical nlp text_mining wiki }
}

@inproceedings{citeulike:2348620,
	title = {Analyzing and Accessing Wikipedia as a Lexical Semantic Resource},
	author = {Torsten Zesch and Iryna Gurevych and Max Mühlhäuser},
	booktitle = {Biannual Conference of the Society for Computational Linguistics and Language Technology},
	school = {Darmstadt University of Technology},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/22d8f740fe023824a89405eaaddc4bfce/renew},
	description = {stuff from citeyoulike},
	abstract = {We analyze Wikipedia as a lexical semantic resource and compare it with conventional resources, such as dictionaries, thesauri, semantic wordnets, etc. Different parts of Wikipedia reflect different aspects of these resources. We show that Wikipedia contains a vast amount of knowledge about, e.g., named entities, domain specific terms, and rare word senses. If Wikipedia is to be used as a lexical semantic resource in large-scale NLP tasks, efficient programmatic access to the knowledge therein is required. We review existing access mechanisms and show that they are limited with respect to performance and the provided access functions. Therefore, we introduce a general purpose, high performance Java-based Wikipedia API that overcomes these limitations. It is available for research purposes at http://www.ukp.tu-darmstadt.de/software/WikipediaAPI.},
	priority = {4}, citeulike-article-id = {2348620},
	keywords = {lexical nlp semantics wikipedia }
}

@inproceedings{citeulike:2348620,
	title = {Analyzing and Accessing Wikipedia as a Lexical Semantic Resource},
	author = {Torsten Zesch and Iryna Gurevych and Max Mühlhäuser},
	booktitle = {Biannual Conference of the Society for Computational Linguistics and Language Technology},
	school = {Darmstadt University of Technology},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/22d8f740fe023824a89405eaaddc4bfce/brightbyte},
	description = {stuff from citeyoulike},
	abstract = {We analyze Wikipedia as a lexical semantic resource and compare it with conventional resources, such as dictionaries, thesauri, semantic wordnets, etc. Different parts of Wikipedia reflect different aspects of these resources. We show that Wikipedia contains a vast amount of knowledge about, e.g., named entities, domain specific terms, and rare word senses. If Wikipedia is to be used as a lexical semantic resource in large-scale NLP tasks, efficient programmatic access to the knowledge therein is required. We review existing access mechanisms and show that they are limited with respect to performance and the provided access functions. Therefore, we introduce a general purpose, high performance Java-based Wikipedia API that overcomes these limitations. It is available for research purposes at http://www.ukp.tu-darmstadt.de/software/WikipediaAPI.},
	priority = {4}, citeulike-article-id = {2348620},
	keywords = {API READ WW-MUST mining nlp semantic wikipedia }
}

@inproceedings{citeulike:2348609,
	title = {Comparing Wikipedia and German Wordnet by Evaluating Semantic Relatedness on Multiple Datasets},
	author = {Torsten Zesch and Iryna Gurevych and Max Mühlhäuser},
	booktitle = {Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT)},
	school = {Darmstadt University of Technology},
	url = {http://elara.tk.informatik.tu-darmstadt.de/publications/2007/hlt-short.pdf},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/20d94192305149e10721d3a8f9ca8bb0a/brightbyte},
	description = {stuff from citeyoulike},
	abstract = {We evaluate semantic relatedness mea- sures on different German datasets show- ing that their performance depends on: (i) the definition of relatedness that was underlying the construction of the evaluation dataset, and (ii) the knowledge source used for computing semantic relatedness. We analyze how the underlying knowledge source influences the performance of a measure. Finally, we investigate the combination of wordnets and Wikipedia to improve the performance of semantic re- latedness measures.},
	priority = {0}, citeulike-article-id = {2348609},
	keywords = {READ WW-MUST relatedness wikipedia wordnet }
}

@inproceedings{GurevychZesch2007,
	title = {Analysis of the Wikipedia Category Graph for NLP Applications},
	author = {Torsten Zesch and Iryna Gurevych},
	booktitle = {Proceedings of the TextGraphs-2 Workshop (NAACL-HLT)},
	school = {Darmstadt University of Technology},
	url = {http://elara.tk.informatik.tu-darmstadt.de/publications/2007/hlt-textgraphs.pdf},
	year = {2007},
	biburl = {http://www.bibsonomy.org/bibtex/2332ed720a72bf069275f93485432314b/brightbyte},
	description = {stuff from citeyoulike},
	abstract = {In this paper, we discuss two graphs in
Wikipedia (i) the article graph, and (ii) the category graph. We perform a graph-theoretic analysis of the category graph, and show that it is a scale-free, small world graph like other well-known lexical semantic networks. We substantiate our findings by transferring semantic relatedness algorithms defined on WordNet to the Wikipedia category graph. To assess the usefulness of the category graph as an NLP resource, we analyze its coverage and the performance of the transferred semantic relatedness algorithms.},
	priority = {3}, citeulike-article-id = {2348605},
	keywords = {READ WW-MUST nlp relatedness semantic wikipedia }
}