Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System
碩士 === 國立臺灣大學 === 資訊工程學研究所 === 97 === There are many restaurants conveniently located in many neighborhoods, as eating out has become an integral part of the modern life. However, deciding what/where to eat can be a challenge for many people. This research develops a restaurant recommendation system...
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ndltd-TW-097NTU053920862016-05-04T04:31:49Z http://ndltd.ncl.edu.tw/handle/60638063184312502841 Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System 情境資訊對智慧型裝置上餐廳推薦系統的影響分析 Chi-Chia Huang 黃啟嘉 碩士 國立臺灣大學 資訊工程學研究所 97 There are many restaurants conveniently located in many neighborhoods, as eating out has become an integral part of the modern life. However, deciding what/where to eat can be a challenge for many people. This research develops a restaurant recommendation system on a mobile phone. Collaborative filtering technique is used to make restaurant recommendations to the users. In addition, contextual information sensed by the smart phone is taken into to consideration to improve the quality of recommendations. In this experiment, data for restaurants around the National Taiwan University campus were collected for two months. Facts and reviews of sixty-eight restaurants were contributed by seventeen test subjects. The results showed significant improvement in recommendation quality when contextual information is applied. For a recommendation list of length six,the accuracy grows from 26% without contextual information to 66% with contextual information. Jane Yung-jen Hsu 許永真 2009 學位論文 ; thesis 62 en_US |
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碩士 === 國立臺灣大學 === 資訊工程學研究所 === 97 === There are many restaurants conveniently located in many neighborhoods, as eating out has become an integral part of the modern life. However, deciding what/where to eat can be a challenge for many people. This research develops a restaurant recommendation system on a mobile phone.
Collaborative filtering technique is used to make restaurant recommendations to the users. In addition, contextual information sensed by the smart phone is taken into to consideration to improve the quality of recommendations.
In this experiment, data for restaurants around the National Taiwan University campus were collected for two months. Facts and reviews of sixty-eight restaurants were contributed by seventeen test subjects. The results showed significant improvement in recommendation quality when contextual information is applied. For a recommendation list of length six,the accuracy grows from 26% without contextual information to 66% with contextual information.
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Jane Yung-jen Hsu |
author_facet |
Jane Yung-jen Hsu Chi-Chia Huang 黃啟嘉 |
author |
Chi-Chia Huang 黃啟嘉 |
spellingShingle |
Chi-Chia Huang 黃啟嘉 Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System |
author_sort |
Chi-Chia Huang |
title |
Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System |
title_short |
Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System |
title_full |
Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System |
title_fullStr |
Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System |
title_full_unstemmed |
Impact Analysis of Contextual Information in a Mobile Restaurant Recommender System |
title_sort |
impact analysis of contextual information in a mobile restaurant recommender system |
publishDate |
2009 |
url |
http://ndltd.ncl.edu.tw/handle/60638063184312502841 |
work_keys_str_mv |
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