Customer satisfaction is getting more and more importance world-wide. Informatics tools and methods are used to research customer satisfaction based on a detailed analysis of consumer reviews. The examined reviews are written in natural languages and some Artificial Intelligence (AI) techniques such as Text Mining, Aspect Sentiment Analysis, Data Mining and Machine Learning are used for the study. As input for running the investigations, we use different internet resources in which the accumulated customer reviews are available. These are for example yelp.com, tripadviser.com and tophotels.ru, etc. To see and show the efficacy of the proposed approach, we have carried out experiments on hotel client satisfaction. The results have proven the effectiveness of the proposed approach to decision support in product quality management and support applying them instead of traditional methods of qualitative and quantitative research of customer satisfaction.
quality management; customer satisfaction research; decision support system; sentiment analysis.
George KOVÁCS, Diana BOGDANOVA, Nafissa YUSSUPOVA, Maxim BOYKO, "Informatics Tools, AI Models and Methods Used for Automatic Analysis of Customer Satisfaction", Studies in Informatics and Control, ISSN 1220-1766, vol. 24(3), pp. 261-270, 2015. https://doi.org/10.24846/v24i3y201503
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