The Comprehensive Review of Novel Data-Mining Approaches for Sentiment Classification In Tourism Applications
European Journal of Molecular & Clinical Medicine,
2020, Volume 7, Issue 9, Pages 2166-2180
AbstractMany places considered as tourist sites have grown rapidly. Many tourists find it difficult to get the right information about the tourist site due to technological advancements.Because there are so many sites that provide user ratings and feedback, not all of them are readable, and it isn't easy to find relevant information to get the overall picture.Communication between emotions and individuals is considered an important aspect of communication.Text emotion extraction is used to determine controlled communication of human-computer interactions and many other people. Emotions also express the basic expressions of a person's face or text through language. Emotions are also expressed in one word or many words.Customers make their own decisions based on existing reviews. Tourists looking for their products or services have many problemsknowing the user attitude from the previous work reviews.Tourism review datasets for simulation analysis are prepared by collecting different reviews from different websites.The sentiment analysis framework is then reviewed, and mining is doneby implementing the Data MiningTechniques that will analyze classes, suggesting a complete vocabulary's strengths and weaknesses. Conceptualization and reputation analysisisconsidered to be the process of automatically extracting and analyzing the opinion, feelings, thoughts, and insights about a particular willachievefrom different facets such as politics, economy, events, phenomena, services, etc.; such emotions are defined as the positive or negative emotions of an individual.The upcoming system willautomatically analyze the emotion with a low analysis time level and provide better accuracy results than the previous system.
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