Acta Polytechnica Hungarica · 2016 · 31 citations · 5 references
ComputingComputer ScienceQuality ManagementArtificial IntelligenceMachine LearningNatural Language ProcessingCustomer SatisfactionCustomer Satisfaction ManagementOpinion MiningSentiment AnalysisService QualityText MiningArtificial Intelligence In HospitalityCustomer Satisfaction AnalyticsCustomer Satisfaction PredictionHospitality Service QualityHotel Data AnalyticsHotel Service QualityReviews
This paper proposes a conceptual approach to the research into customer satisfaction based on a detailed analysis of consumer reviews written in natural languages using Artificial Intelligence (AI) techniques such as Text Mining, Aspect Sentiment Analysis, Data Mining and Machine Learning.Special Internet resources for accumulating customer reviews, such as yelp.com,tripadviser.comand tophotels.ru,are used as data sources.To evaluate the efficacy of the proposed approach, we have carried out an experiment on qualitative and quantitative research of hotel client satisfaction.Even "Big data" applications were taken into account as a possibility to evaluate quality of services.The obtained results prove the effectiveness of the proposed approach to decision support in product quality management and argues for using it instead of classical methods of qualitative and quantitative research into customer satisfaction.
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