Text Classification Using Association Rules, Dependency Pruning and Hyperonymization

2014/01/01 by Yannis Haralambous, Haralambous, Yannis, Philippe Lenca +1
Computer Science · #Computation and Language (cs.CL) #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Information Retrieval (cs.IR) #Rough Sets and Fuzzy Logic #Text and Document Classification Technologies #cs.CL #cs.IR

paper · pdf · doi:10.48550/arxiv.1407.7357

16 pages, 2 figures, presented at DMNLP 2014

arxiv created 2014/07/28 · openalex publication_date 2014/07/28 · arxiv updated 2014/07/29 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28

Abstract

We present new methods for pruning and enhancing item- sets for text classification via association rule mining. Pruning methods are based on dependency syntax and enhancing methods are based on replacing words by their hyperonyms of various orders. We discuss the impact of these methods, compared to pruning based on tfidf rank of words.

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