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

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 rev...

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Main Authors: Tan, Wendy Wei Syn, Bong, Chih How, Issa, Atoum
Format: Proceeding
Language:English
Published: 2014
Subjects:
T Technology (General)
Online Access:http://ir.unimas.my/id/eprint/8454/1/Wendy%20Tan.pdf
http://ir.unimas.my/id/eprint/8454/
http://www.researchgate.net/publication/268445135_Using_Latent_Semantic_Analysis_to_Identify_Quality_in_Use_%28QU%29_Indicators_from_User_Reviews
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id my.unimas.ir.8454
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spelling my.unimas.ir.84542022-01-04T02:57:59Z http://ir.unimas.my/id/eprint/8454/ Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews Tan, Wendy Wei Syn Bong, Chih How Issa, Atoum T Technology (General) 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. 2014 Proceeding NonPeerReviewed text en http://ir.unimas.my/id/eprint/8454/1/Wendy%20Tan.pdf 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). http://www.researchgate.net/publication/268445135_Using_Latent_Semantic_Analysis_to_Identify_Quality_in_Use_%28QU%29_Indicators_from_User_Reviews
institution Universiti Malaysia Sarawak
building Centre for Academic Information Services (CAIS)
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sarawak
content_source UNIMAS Institutional Repository
url_provider http://ir.unimas.my/
language English
topic T Technology (General)
spellingShingle T Technology (General)
Tan, Wendy Wei Syn
Bong, Chih How
Issa, Atoum
Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
description 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.
format Proceeding
author Tan, Wendy Wei Syn
Bong, Chih How
Issa, Atoum
author_facet Tan, Wendy Wei Syn
Bong, Chih How
Issa, Atoum
author_sort Tan, Wendy Wei Syn
title Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
title_short Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
title_full Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
title_fullStr Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
title_full_unstemmed Using Latent Semantic Analysis to Identify Quality in Use (QU) Indicators from User Reviews
title_sort using latent semantic analysis to identify quality in use (qu) indicators from user reviews
publishDate 2014
url http://ir.unimas.my/id/eprint/8454/1/Wendy%20Tan.pdf
http://ir.unimas.my/id/eprint/8454/
http://www.researchgate.net/publication/268445135_Using_Latent_Semantic_Analysis_to_Identify_Quality_in_Use_%28QU%29_Indicators_from_User_Reviews
_version_ 1724078461822173184
score 13.211869

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