Please use this identifier to cite or link to this item:
Title: Keyword extraction strategy for item banks text categorization
Authors: Kanlaya Naruedomkul
Keywords: Feature selection;Item bank;Keyword extraction;Patterned keywords in phrase;Text categorization
Issue Date: 2007
Publisher: 2007 Blackwell Publishing, Inc.
Citation: Computational Intelligence
Abstract: We proposed a feature selection approach, Patterned Keyword in Phrase (PKIP), to text categorization for item banks. The item bank is a collection of textual question items that are short sentences. Each sentence does not contain enough relevant words for directly categorizing by the traditional approaches such as "bag-of-words." Therefore, PKIP was designed to categorize such question item using only available keywords and their patterns. PKIP identifies the appropriate keywords by computing the weight of all words. In this paper, two keyword selection strategies are suggested to ensure the categorization accuracy of PKIP. PKIP was implemented and tested with the item bank of Thai high primary mathematics questions. The test results have proved that PKIP is able to categorize the question items correctly and the two keyword selection strategies can extract the very informative keywords.
ISSN: 08247935
Appears in Collections:Mathematics: International Proceedings

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.