Presenting the model for opinion mining at the document feature level for hotel users' reviews
Subject Areas :
ELHAM KHALAJJ
1
(K.N. Toosi University of Technology)
shahriyar mohammadi
2
(K.N. Toosi University of Technology)
Keywords: Sentiment Analysis, Opinion Mining, Genetic algorithm, Aspect-base Level Analysis, Data Mining.,
Abstract :
Nowadays, online review of user’s sentiments and opinions on the Internet is an important part of the process of people deciding whether to choose a product or use the services provided. Despite the Internet platform and easy access to blogs related to opinions in the field of tourism and hotel industry, there are huge and rich sources of ideas in the form of text that people can use text mining methods to discover the opinions of. Due to the importance of user's sentiments and opinions in the industry, especially in the tourism and hotel industry, the topics of opinion research and analysis of emotions and exploration of texts written by users have been considered by those in charge. In this research, a new and combined method based on a common approach in sentiment analysis, the use of words to produce characteristics for classifying reviews is presented. Thus, the development of two methods of vocabulary construction, one using statistical methods and the other using genetic algorithm is presented. The above words are combined with the Vocabulary of public feeling and standard Liu Bing classification of prominent words to increase the accuracy of classification
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