@inproceedings{Beel2017TFIDu-41879,
  year={2017},
  doi={10.9776/17217},
  title={TF-IDuF : A Novel Term-Weighting Scheme for User Modeling based on Users’ Personal Document Collections},
  url={http://hdl.handle.net/2142/96756},
  publisher={University of Illinois},
  address={Urbana-Champaign},
  booktitle={Proceedings of the iConference 2017, Wuhan, China, 2017},
  pages={452--459},
  author={Beel, Joeran and Langer, Stefan and Gipp, Bela}
}

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    <dc:contributor>Langer, Stefan</dc:contributor>
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    <dcterms:abstract xml:lang="eng">TF-IDF is one of the most popular term-weighting schemes, and is applied by search engines, recommender systems, and user modeling engines. With regard to user modeling and recommender systems, we see two shortcomings of TF-IDF. First, calculating IDF requires access to the document corpus from which recommendations are made. Such access is not always given in a user-modeling or recommender system. Second, TF-IDF ignores information from a user’s personal document collection, which could – so we hypothesize – enhance the user modeling process. In this paper, we introduce TF-IDuF as a term-weighting scheme that does not require access to the general document corpus and that considers information from the users’ personal document collections. We evaluated the effectiveness of TF-IDuF compared to TF-IDF and TF-Only and found that TF-IDF and TF-IDuF perform similarly (click-through rates (CTR) of 5.09% vs. 5.14%), and both are around 25% more effective than TF-Only (CTR of 4.06%) for recommending research papers. Consequently, we conclude that TF-IDuF could be a promising term-weighting scheme, especially when access to the document corpus for recommendations is not possible, and thus classic IDF cannot be computed. It is also notable that TF-IDuF and TF-IDF are not exclusive, so that both metrics may be combined to a more effective term-weighting scheme.</dcterms:abstract>
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    <dc:creator>Gipp, Bela</dc:creator>
    <dc:creator>Langer, Stefan</dc:creator>
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    <dc:contributor>Gipp, Bela</dc:contributor>
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