Using Mobile App For Personalized Hotel Recommendation
碩士 === 國立中山大學 === 資訊管理學系研究所 === 104 === 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...
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ndltd-TW-104NSYS53960732019-05-15T23:01:39Z http://ndltd.ncl.edu.tw/handle/67wyrf Using Mobile App For Personalized Hotel Recommendation 運用文字探勘技術與行動載具進行個人化旅館的推薦系統 Po-Chang Chen 陳柏璋 碩士 國立中山大學 資訊管理學系研究所 104 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. S.Y. Hwang Keng-Pei Lin 黃三益 林耕霈 2016 學位論文 ; thesis 57 en_US |
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碩士 === 國立中山大學 === 資訊管理學系研究所 === 104 === 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.
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author2 |
S.Y. Hwang |
author_facet |
S.Y. Hwang Po-Chang Chen 陳柏璋 |
author |
Po-Chang Chen 陳柏璋 |
spellingShingle |
Po-Chang Chen 陳柏璋 Using Mobile App For Personalized Hotel Recommendation |
author_sort |
Po-Chang Chen |
title |
Using Mobile App For Personalized Hotel Recommendation |
title_short |
Using Mobile App For Personalized Hotel Recommendation |
title_full |
Using Mobile App For Personalized Hotel Recommendation |
title_fullStr |
Using Mobile App For Personalized Hotel Recommendation |
title_full_unstemmed |
Using Mobile App For Personalized Hotel Recommendation |
title_sort |
using mobile app for personalized hotel recommendation |
publishDate |
2016 |
url |
http://ndltd.ncl.edu.tw/handle/67wyrf |
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