Informatics Tools, AI Models and Methods Used for Automatic Analysis of Customer Satisfaction

satisfaction indices make it difficult to understand, compare and interpret the results. Methods of analysis of data collected through the recommended ISO 10004 procedures permit only the detection of linear dependencies. To increase the effectiveness of product quality management, we suggest approaching the research of customer satisfaction through the use of Informatics, as AI technologies. Applying Text Mining tools for analyzing customers’ reviews posted on the Internet is not novel. There are many studies concerning models and methods for data collection, sentiment analysis and information extraction. Recent studies show acceptable accuracy of methods for sentiment classification. Gräbner Studies in Informatics and Control, Vol. 24, No. 3, September 2015 http://www.sic.ici.ro 261 Informatics Tools, AI Models and Methods Used for Automatic Analysis of Customer Satisfaction George KOVÁCS, Diana BOGDANOVA, Nafissa YUSSUPOVA, Maxim BOYKO 1 Computer and Automation Research Institute, Kende u. 13-17, Budapest, 1111, Hungary, kovacs.gyorgy@sztaki.mta.hu 2 Ufa State Aviation Technical University, K. Marx 12, Ufa, 450000, Russia, dianochka7bog@mail.ru, yussupova@ugatu.ac.ru, maxim.boyko87@gmail.com Abstract: Customer satisfaction is getting more and more importance world-wide. Informatics tools and methods are 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.