Text Item Classification Task

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A text item classification ask is a linguistic classification task whose input is a text item (whose class set is a document category set).






  • (Sebastiani, 2002) ⇒ Fabrizio Sebastiani. (2002). "Machine Learning in Automated Text Categorization." In: Association of Computing Machinery Computing Surveys (CSUR), 34(1).
    • The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last 10 years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories.


  • (Yang, 1999) ⇒ Y. Yang. (1999). "An Evaluation of Statistical Approaches to Text Categorization." In: Journal of Information Retrieval, 1.
    • NOTE: it experiments on a search space of ~18,000 Medical Subject Headings (MeSH).



  • (Wilbur & Yang, 1996) ⇒ J. Wilbur, and Y. Yang. (1996). "Analysis of Statistical Term Strength and its Use in the Indexing and Retrieval of Molecular Biology Texts." In: Comput. Biol. Med., 26(3), 209–222.
    • experiment on a search space of less than 18,000 Medical Subject Headings (MeSH).


  • (Yang & Chute, 1992) ⇒ Y. Yang, and C. Chute. (1992). “A Linear Least Squares Fit Mapping Method for Information Retrieval from Natural Language Texts." In: COLING 1992.
    • Work with the International Classification of Diseases (about 12,000 concepts)


  • (Field, 1975) ⇒ B. J. Field. (1975). "Towards Automatic Indexing: Automatic assignment of controlled-language indexing and classification from free indexing." In: : Journal of Documentation, 31(4). doi:10.1108/eb026605


  • (Borko & Bernick, 1963) ⇒ Harold Borko, and Myrna Bernick. (1963). "Automatic Document Classification." In: Journal of the ACM (JACM).
    • The problem of automatic document classification is a part of the larger problem of automatic content analysis. Classification means the determination of subject content. For a document to be classified under a given heading, it must be ascertained that its subject matter relates to that area of discourse. In most cases this is a relatively easy decision for a human being to make. The question being raised is whether a computer can be programmed to determine the subject content of a document and the category (categories) into which it should be classified.