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- KUO Wei-Ti
- National Taiwan University, Taipei, Taiwan
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- KUO Yen-Ling
- National Taiwan University, Taipei, Taiwan
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- HSU Jane Yung-jen
- National Taiwan University, Taipei, Taiwan
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- TSAI Richard Tzong-Han
- Yuan Ze University, Taoyuan, Taiwan
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説明
<p> In the past, there are a great many research about restaurant recommendation. Most of them focus on location-based methods, and the scenario is usually simple. It's easy to recommend neighboring and price accepted restaurants to people, however, there are very few research considering many event contexts such like purposes, companions, and festivals, etc. In addition to the types of cuisine and price, we even consider the atmosphere and style of restaurants. Unlike the much more extensively researched explicit feedback, we don't have any direct rating from the user regarding their preference. Namely, we lack the substantial evidence on which restaurants user dislike. Contrast to other domains, the lack of booking information is a more severe problem. This research aims at how to use the available data to provide useful recommendation. In this work, we use the data between August of 2008 and December of 2011 from EZTABLE which is an online restaurant booking system in Taiwan, to discover how the event contexts affect restaurant recommendation.</p>
収録刊行物
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- 人工知能学会全国大会論文集
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人工知能学会全国大会論文集 JSAI2012 (0), 3M2IOS3b6-3M2IOS3b6, 2012
一般社団法人 人工知能学会
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詳細情報 詳細情報について
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- CRID
- 1390845712978824064
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- NII論文ID
- 130007426961
- 40020293755
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- NII書誌ID
- AA11578981
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- ISSN
- 13479881
- 27587347
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- NDL書誌ID
- 025967571
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDLサーチ
- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可