@inproceedings{mccallum1998naive,
        title = {A Comparison of Event Models for Naive {B}ayes Text Classification},
        author = {Andrew McCallum and Kamal Nigam},
        booktitle = {Learning for Text Categorization: Papers from the 1998 {AAAI} Workshop },
        pages = {41--48},
        year = 1998,
        url = {http://www.kamalnigam.com/papers/multinomial-aaaiws98.pdf},
        biburl = {http://www.bibsonomy.org/bibtex/2fa46d1cc0dd56ab40a7f722e569a1fd3/jil},
	keywords = {multinomial naive event ereignis vergleich classification bernoulli text bayes model}
}

@misc{mccallum-multilabel,
        title = {Multi-Label Text Classification with a Mixture Model Trained by EM},
        author = {Andrew Kachites McCallum},
        year = 1999,
        url = {http://citeseer.ist.psu.edu/mccallum99multilabel.html},
        description = {Multi-Label Text Classification with a Mixture Model Trained by EM (ResearchIndex)},
	biburl = {http://www.bibsonomy.org/bibtex/2c3aac84b0731d074f8923ab1fd6dc1f2/jil},
	keywords = {probabilistisch model native probabilistic classification nativ multilabel bayes}
}

@inproceedings{mika05-ontologies,
        title = {Ontologies Are Us: A Unified Model of Social Networks and Semantics.},
        author = {Peter Mika},
        booktitle = {The Semantic Web - ISWC 2005, Proceedings of the 4th International Semantic Web Conference, ISWC 2005, Galway, Ireland, November 6-10},
        editor = {Yolanda Gil and Enrico Motta and V. Richard Benjamins and Mark A. Musen},
        pages = {522-536},
        publisher = {Springer},
        series = {Lecture Notes in Computer Science},
        volume = 3729,
        year = 2005,
        url = {http://www.cs.vu.nl/~pmika/research/papers/ISWC-folksonomy.pdf},
        lastdatemodified = {2006-09-26},
	longnotes = {[[http://citeseer.ist.psu.edu/739485.html citeseer]]},
	pdf = {mika05-ontologies.pdf},
	read = {notread},
	lastname = {Mika},
	own = {notown},
	abstract = {In our work we extend the traditional bipartite model of ontologies with the social dimension, leading to a tripartite model of actors, concepts and instances. We demonstrate the application of this representation by showing how community-based semantics emerges from this model through a process of graph transformation. We illustrate ontology emergence by two case studies, an analysis of a large scale folksonomy system and a novel method for the extraction of community-based ontologies from Web pages.},
	biburl = {http://www.bibsonomy.org/bibtex/2426c2fd559bb4e41c4f67d4eed0a39c7/jil},
	keywords = {learning extension erweiterung 2005 ontology ontologie model mika folksonomy}
}