Enhancement of relevant features for text mining

Albathan, Mubarak Murdi M. (2015) Enhancement of relevant features for text mining. PhD thesis, Queensland University of Technology.

Abstract

With the explosion of information resources, there is an imminent need to understand interesting text features or topics in massive text information. This thesis proposes a theoretical model to accurately weight specific text features, such as patterns and n-grams. The proposed model achieves impressive performance in two data collections, Reuters Corpus Volume 1 (RCV1) and Reuters 21578.

Impact and interest:

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Full-text downloads:

33 since deposited on 11 Jan 2016
27 in the past twelve months

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ID Code: 90072
Item Type: QUT Thesis (PhD)
Supervisor: Li, Yuefeng, Xu, Yue, & Tao, Daniel
Keywords: Text Mining, Feature Selection, Information retrieval, Data Mining, pattern mining
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 11 Jan 2016 02:52
Last Modified: 11 Jan 2016 02:53

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