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Ranking Based Opinion Mining in Myanmar Travel Domain

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Genetic and Evolutionary Computing (ICGEC 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1107))

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Abstract

The travel and tour industry is one of the world’s largest service industries. It takes part as a vital role of state’s economy for the developing countries like Myanmar. Therefore, a travel information support system becomes essential that construction of Myanmar travel domain has been considered to be developed which is enriching with ancient heritage and known for many natural tourist destinations. Besides, it extracts travelers’ opinions with a purpose of promoting and improving all related services. We intend to implement the ontology-based opinion mining for Myanmar travel domain. The main contribution of this paper is collecting valuable travel information and tourists’ opinions of Myanmar by crowd sourcing method which has to be used for ranking based opinion mining to support travelers. This proposed method is important for travel industry in terms of services quality, promotion of the business and facilitate the industry that can be ranked based on the factors of determining many various opinions. Thus, opinion mining is affected not only the review comments created by visitors, but also the ranking of travel items given by every stake holder in the industry.

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References

  1. Bakka, J., Bahaj, M.: Generating of RDF graph from a relational database using Jena API. Int. J. Eng. Technol. (IJET) 5(2), 1970–1975 (2013). ISSN 0975-4024

    Google Scholar 

  2. Baranikumar, P., Gobi, N.: Feature extraction of opinion mining using ontology. Int. J. Adv. Comput. Electr. Eng. 1(1), 18–22 (2016)

    Google Scholar 

  3. Boumlik, A., Bahaj, M.: Advanced set of rules to generate ontology from relational database. J. Softw. 11(1), 27–43 (2016)

    Article  Google Scholar 

  4. Bucur, C.: Using opinion mining techniques in tourism. Proc. Econ. Finance 23, 1666–1673 (2015)

    Article  Google Scholar 

  5. Chinsha, T.C., Joseph, S.: Aspect based opinion mining from restaurant reviews. In: Advanced Computing and Communication Techniques for High Performance Applications (ICACCTHPA-2014) (2014). ISSN 0975–8887. Int. J. Comput. Appl.

    Google Scholar 

  6. Khruahong, S., Kong, X., Hoang, D.: Ontology design for Thailand travel industry. Int. J. Knowl. Eng. 1(3), 191–196 (2015)

    Article  Google Scholar 

  7. Liu, B.: Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers, San Rafael (2012)

    Google Scholar 

  8. Shepelenko, O.: Opinion mining and sentiment analysis using Bayesian and neural networks approaches. Master thesis, University of Tartu, Institute of Computer Science (2017)

    Google Scholar 

  9. Sivula, A., Kantola, J.: Ontology focused crowdsourcing management. In: 6th International Conference on Applied Human Factors and Ergonomic and the Affiliated Conferences, pp. 632–638 (2015)

    Article  Google Scholar 

  10. Somantri, O., Apriliani, D.: Opinion mining on culinary food customer satisfaction using Naïve Bayes based-on hybrid feature selection. Indonesian J. Electr. Eng. Comput. Sci. 15(1), 468–475 (2019)

    Article  Google Scholar 

  11. Vidushi, Sodhi G.S.: Sentiment mining of online reviews using machine learning algorithms. Int. J. Eng. Devel. Res. IJEDR 5(2), 1321–1334 (2017)

    Google Scholar 

  12. World Travel and Tourism Council: Travel and Tourism Economic Impact 2019 (2019)

    Google Scholar 

  13. Travel & Tourism Economic Impact (2017). https://www.wttc.org/-/media/files/reports/economic-impact-research/regions-2017/world2017.pdf. Accessed 30 Sept 2017

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Author information

Authors and Affiliations

  1. University of Computer Studies, Yangon, Myanmar

    Nilar Aye

  2. University of Computer Studies, Taunggyi, Myanmar

    Thinn Thu Naing

Authors
  1. Nilar Aye
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  2. Thinn Thu Naing
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Corresponding author

Correspondence to Nilar Aye .

Editor information

Editors and Affiliations

  1. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

    Jeng-Shyang Pan

  2. Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway

    Jerry Chun-Wei Lin

  3. College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao, China

    Yongquan Liang

  4. School of Computer Science, Engineering and Mathematics, Flinders University, Bedford Park, Australia

    Shu-Chuan Chu

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Aye, N., Naing, T.T. (2020). Ranking Based Opinion Mining in Myanmar Travel Domain. In: Pan, JS., Lin, JW., Liang, Y., Chu, SC. (eds) Genetic and Evolutionary Computing. ICGEC 2019. Advances in Intelligent Systems and Computing, vol 1107. Springer, Singapore. https://doi.org/10.1007/978-981-15-3308-2_4

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