Publication statistics

Pub. period:2004-2006
Pub. count:5
Number of co-authors:6


Number of publications with 3 favourite co-authors:

Sean M. McNee:
Joseph A. Konstan:
Harold Boley:



Productive colleagues

Georg Lausen's 3 most productive colleagues in number of publications:

Joseph A. Konstan:47
Lars Schmidt-Thiem..:9
Cai-Nicolas Ziegle..:7

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Georg Lausen


Publications by Georg Lausen (bibliography)

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Ziegler, Cai-Nicolas, Simon, Kai and Lausen, Georg (2006): Automatic computation of semantic proximity using taxonomic knowledge. In: Yu, Philip S., Tsotras, Vassilis J., Fox, Edward A. and Liu, Bing (eds.) Proceedings of the 2006 ACM CIKM International Conference on Information and Knowledge Management November 6-11, 2006, Arlington, Virginia, USA. pp. 465-474.

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Simon, Kai, Lausen, Georg and Boley, Harold (2006): From HTML documents to web tables and rules. In: Fox, Mark S. and Spencer, Bruce (eds.) Proceedings of the 8th International Conference on Electronic Commerce - ICEC 2006 2006, Fredericton, New Brunswick, Canada. pp. 125-131.

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Simon, Kai and Lausen, Georg (2005): ViPER: augmenting automatic information extraction with visual perceptions. In: Herzog, Otthein, Schek, Hans-Jorg and Fuhr, Norbert (eds.) Proceedings of the 2005 ACM CIKM International Conference on Information and Knowledge Management October 31 - November 5, 2005, Bremen, Germany. pp. 381-388.

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Ziegler, Cai-Nicolas, McNee, Sean M., Konstan, Joseph A. and Lausen, Georg (2005): Improving recommendation lists through topic diversification. In: Proceedings of the 2005 International Conference on the World Wide Web 2005. pp. 22-32.

In this work we present topic diversification, a novel method designed to balance and diversify personalized recommendation lists in order to reflect the user's complete spectrum of interests. Though being detrimental to average accuracy, we show that our method improves user satisfaction with recommendation lists, in particular for lists generated using the common item-based collaborative filtering algorithm. Our work builds upon prior research on recommender systems, looking at properties of recommendation lists as entities in their own right rather than specifically focusing on the accuracy of individual recommendations. We introduce the intra-list similarity metric to assess the topical diversity of recommendation lists and the topic diversification approach for decreasing the intra-list similarity. We evaluate our method using book recommendation data, including offline analysis on 361,349 ratings and an online study involving more than 2,100 subjects.

© All rights reserved Ziegler et al. and/or ACM Press

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Ziegler, Cai-Nicolas, Lausen, Georg and Schmidt-Thieme, Lars (2004): Taxonomy-driven computation of product recommendations. In: Grossman, David A., Gravano, Luis, Zhai, Chengxiang, Herzog, Otthein and Evans, David A. (eds.) Proceedings of the 2004 ACM CIKM International Conference on Information and Knowledge Management November 8-13, 2004, Washington, DC, USA. pp. 406-415.

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