Abstract
This paper introduces a process for online travel review analysis in Thai language employed in a recommender system supporting travelers (TRAS). The process covers three main categories: attractions, accommodation, and gastronomy. The filtering and queuing results gained with MapReduce build the input for three main steps: (1) the analysis process for element scores, (2) the analysis process for the total scores of the reviews, and (3) the travel guidance system based on users’ selections. The extensive tests revealed that the system operates properly regarding functional and non-functional requirements. We employed 60,000 travel reviews containing all categories to test the analysis process for steps (1) and (2). We found that the number of adjectives and modifiers in each review affects the time used for analysis. In contrast to previous recommender systems, TRAS applies a more diverse and transparent rating and ranking approach. Travelers can select the features they are interested in and get personalized results, so that a given location might achieve different rankings for different travelers.
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References
Snae, C., Pawarawat, N.: A study of internet user behaviour using techniques of data mining and temporal ontology. In: The Third Naresuan Research Conference, Phitsanulok, Thailand, 28–29 July 2007 (2007). (in Thailand)
Snae, C., Brückner, M.: Data cleaning and clustering of internet log files based on a temporal ontology. In: The Third Mahasarakham International Workshop on AI (MIWAI 2009) (2009)
Kitwattanathaworn, P., Angsakul, T., Angsakul, C.: Knowledge extraction system from online hotel review using fuzzy logic. J. KMUTNB 23(2), 363–377 (2013)
Chotirat, W., Boonrawd, P., Wichian, S.N.: Developing an ontology knowledge based for automatic online news analysis. Inf. Technol. J. 7(14), 13–18 (2011)
Hu, M., Liu, B.: Mining and summarizing customer reviews. In: Proceedings of the 2004 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 168–177 (2004)
Jian, M.S., Fang, Y.C., Wang, Y.K., Cheng, C.: Big data analysis in hotel customer response and evaluation based on cloud. In: 19th International Conference on Advanced Communication Technology (ICACT) (2017). https://ieeexplore.ieee.org/document/7890201/. Accessed 21 Aug 2018
Bhosale, H.S., Gadekar, D.P.: A review paper on big data and hadoop. Int. J. Sci. Res. Publ. 4(10), 1–7 (2014)
Dhawan, S., Rathee, S.: Big data analytics using hadoop components like pig and hive. Am. Int. J. Res. Sci., Technol., Eng. Math. (AIJRSTEM) 2, 88–93 (2013)
Thusoo, A., et al.: Hive - a warehousing solution over a map-reduce framework (2009). https://research.facebook.com/publications/hive-a-warehousing-solution-over-a-map-reduce-framework/. Accessed 18 July 2018
Namahoot, C.S., Panawong, N., Brückner, M.: A tourism recommendation system for thailand using semantic web rule language and K-NN algorithm. INFORMATION 19(7), 3017–3024 (2016)
Namahoot, C.S., Brückner, M., Panawong, N.: Context-aware tourism recommender system using temporal ontology and Naïve Bayes. In: Unger, H., Meesad, P., Boonkrong, S. (eds.) Recent Advances in Information and Communication Technology 2015. AISC, vol. 361, pp. 183–194. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-19024-2_19
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Namahoot, C.S., Pinijkitcharoenkul, S., Brückner, M. (2018). Travel Review Analysis System with Big Data (TRAS). In: Qiu, M. (eds) Smart Computing and Communication. SmartCom 2018. Lecture Notes in Computer Science(), vol 11344. Springer, Cham. https://doi.org/10.1007/978-3-030-05755-8_3
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DOI: https://doi.org/10.1007/978-3-030-05755-8_3
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