|Author's Email Address
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|Type of Document
||Using Mobile App For Personalized Hotel Recommendation|
|Date of Defense
Part Of Speech Tagging
||With the advance of mobile devices, the ways people use Internet have changed enormously. Mobile devices are capable of recording users’ behavior, such as locations visited, frequent online shopping stores, browsing history, and so on. The aim of this study is to utilize users’ browsing data on mobile devices and subsequently applying text mining techniques to recommend hotels to users.|
Specifically, we design and implement an APP that allows its user to browse hotel reviews and records every gesture the user has performed. We then identified a subset of hotel reviews that the given user have shown interests depending on the different kinds of gestures he/she has performed. Text mining techniques are subsequently applied to construct the interest profile of the user based on the review content.
We collect 10,690 reviews of 360 hotels in Taiwan. 18 users are recruited to use our proposed APP and participate in the experiment. Experimental result demonstrates that our system have better performance than other approaches.
||Chih-Ping Wei - chair|
T. M. Chang - co-chair
Yuling Hsueh - co-chair
Keng-Pei Lin - advisor
S.Y. Hwang - advisor
Indicate in-campus at 0 year and off-campus access at 5 year.|
|Date of Submission