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...
| Main Authors: | , , |
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| Format: | Proceeding |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/8454/ http://ir.unimas.my/id/eprint/8454/1/Wendy%20Tan.pdf |
| _version_ | 1848836379565359104 |
|---|---|
| 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 |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T06:22:50Z |
| format | Proceeding |
| id | unimas-8454 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:22:50Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-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 |
| 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 |
| title | 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_short | 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 |
| topic | T Technology (General) |
| url | http://ir.unimas.my/id/eprint/8454/ http://ir.unimas.my/id/eprint/8454/ http://ir.unimas.my/id/eprint/8454/1/Wendy%20Tan.pdf |