Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/86400
Título: An expert system for extracting knowledge from customers’ reviews
Autor: Castelli, Mauro
Manzoni, Luca
Vanneschi, Leonardo
Popovič, Aleš
Palavras-chave: Customers’ feedback
E-commerce
Genetic programming
Semantics
Engineering(all)
Computer Science Applications
Artificial Intelligence
Data: 30-Out-2017
Resumo: E-commerce has proliferated in the daily activities of end-consumers and firms alike. For firms, consumer satisfaction is an important indicator of e-commerce success. Today, consumers’ reviews and feedback are increasingly shaping consumer intentions regarding new purchases and repeated purchases, while helping to attract new customers. In our work, we use an expert system to predict the sentiment of a product considering a subset of available customers’ reviews.
Descrição: Castelli, M., Manzoni, L., Vanneschi, L., & Popovič, A. (2017). An expert system for extracting knowledge from customers’ reviews: The case of Amazon.com, Inc. Expert Systems with Applications, 84(October), 117-126. https://doi.org/10.1016/j.eswa.2017.05.008 ---%ABS3%
Peer review: yes
URI: http://www.scopus.com/inward/record.url?scp=85019055201&partnerID=8YFLogxK
http://hdl.handle.net/10362/86400
DOI: https://doi.org/10.1016/j.eswa.2017.05.008
ISSN: 0957-4174
Aparece nas colecções:NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)

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