Creating and visualizing fuzzy document classification

Authors:
Judith Gelernter;Dong Cao;Raymond Lu;Eugene Fink;Jaime G. Carbonell
Affiliations:
School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

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Abstract

Fuzzy classification ranks items by degree rather than assigning them either within or without of a category. The novelty of our work is in integrating fuzzy classification algorithms with an interface to visualize fuzzy results. An advantage of our algorithms' 'fuzziness' is that it provides additional information per retrieved result that helps in deciding whether to drill down to the document or skip it. An advantage of our interface is that it allows users to visualize those differences quickly. We have created a prototype that allows the retrieval of journal articles by content word or by ontology-supported browse categories that can be selected independently or in tandem. Journal articles in our digital library pertain to paleontology, but techniques demonstrated viable in indexing and ranking paleo-journal literature should apply to other knowledge domains with little modification.