IJIRST (International Journal for Innovative Research in Science & Technology)ISSN (online) : 2349-6010

 International Journal for Innovative Research in Science & Technology

Opinion Mining on Tourism


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International Journal for Innovative Research in Science & Technology
Volume 3 Issue - 8
Year of Publication : 2017
Authors : S. Kavitha ; S. Sathyavathi; S. Prabhakaran; S. Swathi; R. Rajkumar

BibTeX:

@article{IJIRSTV3I8073,
     title={Opinion Mining on Tourism},
     author={S. Kavitha, S. Sathyavathi, S. Prabhakaran, S. Swathi and R. Rajkumar},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={8},
     pages={128--131},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I8073.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}



Abstract:

Online tourism forums and social networks have become the most popular platform for sharing tourism related information, with enormous numbers of reviews posted daily. This paper proposes a platform for extraction and summarizing of opinions expressed by users in tourism related online platforms. Extracting opinions from user generated reviews are useful for clients looking for accommodation with the suitable climate and the affordable money. The proposed system extract the reviews from internet mainly focused on twitter and classify them, using an opinion mining technique. Platform is evaluated using a manually pre-classified dataset of user reviews. The proposed system retrieves a collection of reviews about tourist locations posted as tweets in twitter. The client enters the location that he wants to search and the month as an input through the application. The opinion of the people about that particular tourist spot is analysed using rapid miner and their sentiments are classified as positive, negative, neutral and suggested to the people. For classification, the classification algorithm named support vector machine(SVM) have been used. Finally, the recommended locations for the specified month have also been suggested to the client.


Keywords:

Opinion Mining, Opinion Mining on Tourism


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