Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews

Tan, Wendy Wei Syn and Bong, Chih How and Issa, Atoum (2014) Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews. In: The International Conference on Artificial Intelligence and Pattern Recognition (AIPR2014), 11/2014, Asia Pacific University of Technology & Innovation (APU).

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Official URL: http://www.researchgate.net/publication/268445135_...

Abstract

The paper describes a novel approach to categorize users’ reviews according to the three Quality in Use (QU) indicators defined in ISO: effectiveness, efficiency and freedom from risk. With the tremendous amount of reviews published each day, there is a need to automatically summarize user reviews to inform us if any of the software able to meet requirement of a company according to the quality requirements. We implemented the method of Latent Semantic Analysis (LSA) and its subspace to predict QU indicators. We build a reduced dimensionality universal semantic space from Information System journals and Amazon reviews. Next, we projected set of indicators’ measurement scales into the universal semantic space and represent them as subspace. In the subspace, we can map similar measurement scales to the unseen reviews and predict the QU indicators. Our preliminary study able to obtain the average of Fmeasure, 0.3627.

Item Type: Proceeding (Paper)
Uncontrolled Keywords: quality in use, Latent Semantic Analysis, intelligent information system, reviews, data mining, unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: T Technology > T Technology (General)
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 03 Aug 2015 07:31
Last Modified: 03 Aug 2015 07:31
URI: http://ir.unimas.my/id/eprint/8454

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