Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Information Processing and Management: an International Journal
Automatic structuring and retrieval of large text files
Communications of the ACM
A theory of term weighting based on exploratory data analysis
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
A vector space model for automatic indexing
Communications of the ACM
Weighted self-organizing maps: incorporating user feedback
ICANN/ICONIP'03 Proceedings of the 2003 joint international conference on Artificial neural networks and neural information processing
Towards user-adaptive structuring and organization of music collections
AMR'08 Proceedings of the 6th international conference on Adaptive Multimedia Retrieval: identifying, Summarizing, and Recommending Image and Music
Similarity adaptation in an exploratory retrieval scenario
AMR'10 Proceedings of the 8th international conference on Adaptive Multimedia Retrieval: context, exploration, and fusion
An experimental comparison of similarity adaptation approaches
AMR'11 Proceedings of the 9th international conference on Adaptive Multimedia Retrieval: large-scale multimedia retrieval and evaluation
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Automatic structuring is one means to ease access to document collections, be it for organization or for exploration. Of even greater help would be a presentation that adapts to the user's way of structuring and thus is intuitively understandable. We extend an existing user-adaptive prototype system that is based on a growing self-organizing map and that learns a feature weighting scheme from a user's interaction with the system resulting in a personalized similarity measure. The proposed approach for adapting the feature weights targets certain problems of previously used heuristics. The revised adaptation method is based on quadratic optimization and thus we are able to pose certain contraints on the derived weighting scheme. Moreover, thus it is guaranteed that an optimal weighting scheme is found if one exists. The proposed approach is evaluated by simulating user interaction with the system on two text datasets: one artificial data set that is used to analyze the performance for different user types and a real world data set --- a subset of the banksearch dataset --- containing additional class information.