[u' @incollection{sixto_analysing_2013, series = {Lecture {Notes} in {Computer} {Science}}, title = {Analysing {Customers} {Sentiments}: {An} {Approach} to {Opinion} {Mining} and {Classification} of {Online} {Hotel} {Reviews}}, copyright = {\xa92013 Springer-Verlag Berlin Heidelberg}, isbn = {978-3-642-38823-1 978-3-642-38824-8}, shorttitle = {Analysing {Customers} {Sentiments}}, url = {http://link.springer.com/chapter/10.1007/978-3-642-38824-8_38}, abstract = {Customer opinion holds a very important place in products and service business, especially for companies and potential customers. In the last years, opinions have become yet more important due to global Internet usage as opinions pool. Unfortunately , looking through customer reviews and extracting information to improve their service is a difficult work due to the large number of existing reviews. In this work we present a system designed to mine client opinions, classify them as positive or negative, and classify them according to the hotel features they belong to. To obtain this classification we use a machine learning classifier, reinforced with lexical resources to extract polarity and a specialized hotel features taxonomy.}, number = {7934}, urldate = {2013-09-18}, booktitle = {Natural {Language} {Processing} and {Information} {Systems}}, publisher = {Springer Berlin Heidelberg}, author = {Sixto, Juan and Almeida, Aitor and L\xf3pez-de-Ipi\xf1a, Diego}, editor = {M\xe9tais, Elisabeth and Meziane, Farid and Saraee, Mohamad and Sugumaran, Vijayan and Vadera, Sunil}, month = jan, year = {2013}, keywords = {Artificial Intelligence, Data analysis, ISI, NLP, Natural language processing, Social Data Mining, core-c, data mining, hotels, machine learning, opinion mining, thofu}, pages = {359--362}, } ']