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- W3211032949 abstract "In Natural Language Processing, text classification involves the process of categorizing documents into organized groups. Classifiers are trained to analyze the documents and categorize them into groups based on pre-defined tags. In this paper, a framework has been devised to extract features from the text documents. The documents are preprocessed, tagged and then the features are extracted. Preprocessing includes removal of stop words, punctuations. Preprocessed Words were tagged under two categories, Noun and Verb. Tagging of words was based on morphophonemic rules pertaining to Tamil Language. Feature extraction is based on frequency of the occurrences of words tagged as Noun. Extraction of features through the proposed framework enhances dimensionality reduction of data considered for classification process." @default.
- W3211032949 created "2021-11-08" @default.
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- W3211032949 date "2021-01-01" @default.
- W3211032949 modified "2023-09-25" @default.
- W3211032949 title "Frequency Based Feature Extraction Technique for Text Documents in Tamil Language" @default.
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- W3211032949 doi "https://doi.org/10.1007/978-3-030-88244-0_8" @default.
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