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

Autor:	Syn, Wendy Tan Wei, How, Bong Chih, Atoum, Issa
Rok vydání:	2015
Předmět:	Computer Science - Computation and Language Computer Science - Artificial Intelligence Computer Science - Information Retrieval
Druh dokumentu:	Working Paper
Popis:	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 F-measure, 0.3627. Comment: 4 Figures in The International Conference on Artificial Intelligence and Pattern Recognition (AIPR2014),2014
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1503.07294 Zobrazit plný text záznamu View this record from Arxiv