Creating a document model for efficient keyword search is a long studied problem in Information Retrieval. In this paper we explore the application of Tolerance Rough Set Model for Documents (TRSM) for this problem. We further provide an extension of TRSM with a weight learning procedure (TRSM-WL) and compare performance of these two algorithms in keyword search. We further provide a generalization of TRSM-WL that imposes additional constraints on the underlying model structure and compare it to a supervised variant of Explicit Semantic Analysis. © 2013 Springer-Verlag.
CITATION STYLE
Świeboda, W., Meina, M., & Nguyen, H. S. (2013). Weight learning for document tolerance rough set model. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8171 LNAI, pp. 385–396). https://doi.org/10.1007/978-3-642-41299-8_37
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