Composite Feature Extraction and Selection for Text Classification

Although words are basic semantic units in text, phrases, and expressions contain additional information, which is important for text classification. To capture this information, traditional algorithms extract composite features via word sequences or co-occurrences, such as bigrams and termsets, but...

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Veröffentlicht in:	IEEE access 2019, Vol.7, p.35208-35219
Hauptverfasser:	Wan, Chuan, Wang, Yuling, Liu, Yaoze, Ji, Jinchao, Feng, Guozhong
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Classification Composite feature extraction composite feature selection Correlation Data mining Feature extraction Measurement Redundancy Semantics Support vector machines text classification Training Words (language)
Online-Zugang:	Volltext
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