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Kern Roman, Seifert Christin, Zechner Mario, Granitzer Michael

Vote/Veto Meta-Classifier for Authorship Identification

CLEF 2011: Proceedings of the 2011 Conference on Multilingual and Multimodal Information Access Evaluation (Lab and Workshop Notebook Papers), Amsterdam, The Netherlands, 2011

For the PAN 2011 authorship identification challenge we have developeda system based on a meta-classifier which selectively uses the results ofmultiple base classifiers. In addition we also performed feature engineering basedon the given domain of e-mails. We present our system as well as results on theevaluation dataset. Our system performed second and third best in the authorshipattribution task on the large data sets, and ranked middle for the small data set inthe attribution task and in the verification task.

Kern Roman, Zechner Mario, Granitzer Michael

Model Selection Strategies for Author Disambiguation

IEEE Computer Society: 8th International Workshop on Text-based Information Retrieval in Procceedings of 22th International Conference on Database and Expert Systems Applications (DEXA 11), IEEE , 2011

Author disambiguation is a prerequisite for utilizingbibliographic metadata in citation analysis. Automaticdisambiguation algorithms mostly rely on cluster-based disambiguationstrategies for identifying unique authors given theirnames and publications. However, most approaches rely onknowing the correct number of unique authors a-priori, whichis rarely the case in real world settings. In this publicationwe analyse cluster-based disambiguation strategies and developa model selection method to estimate the number of distinctauthors based on co-authorship networks. We show that, givenclean textual features, the developed model selection methodprovides accurate guesses of the number of unique authors.
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