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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
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dc.contributor.advisor | 徐宏民(Winston H. Hsu) | |
dc.contributor.author | An-Jung Cheng | en |
dc.contributor.author | 鄭安容 | zh_TW |
dc.date.accessioned | 2021-06-08T06:24:44Z | - |
dc.date.copyright | 2011-08-08 | |
dc.date.issued | 2011 | |
dc.date.submitted | 2011-08-03 | |
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dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/25685 | - |
dc.description.abstract | 隨著社群網站的蓬勃發展,這些由使用者提供的資料(如:部落格,GPS軌跡和具有地理位置的照片)內含了豐富的資訊,如使用者所標注的文字描述、拍攝時間、地理位置等,有助於多媒體應用的發展,其中,和人的生活習習相關的就是旅遊推薦系統。在這篇論文中,我們著重在如何利用這些社群媒體照片在個人化的旅遊建議架構上。為了達到個人化的目的,我們考慮使用者提供的個人屬性,如性別、種族、年紀等,除了從大量的旅遊移動紀錄裡分析景點間的移動頻率之外,我們還考量照片中自動偵測的人物屬性,採取機率化的貝氏學習模型,應用於行動裝置上的即時個人化旅行建議的架構。為了更進一步顯示人的屬性對旅遊推薦的影響,我們還藉由信息理論的分析方法,證實人的屬性對於個人化的旅遊建議的應用上是有效且有意義的。此外,我們也發現不同屬性群體之間,展現在景點和旅遊路徑上的行為模式也有所不同。
我們從照片分享網站上蒐集全球十九個主要城市裡,有地理位置資訊的照片,總計來說,共有一千多萬張的照片做為我們的實驗資料集。由實驗證實,照片內的人物屬性對於前面所述的推薦架構是非常有前景的,而且也可以提升個人化旅遊推薦的準確度,特別是在困難的預測條件下,更能顯示人物屬性的效果。 | zh_TW |
dc.description.abstract | Leveraging community-contributed data (e.g., blogs, GPS logs, and geo-tagged photos) for travel recommendation is one of the active researches since there are rich contexts and trip activities in such explosively growing data. In this work, we focus on personalized travel recommendation by leveraging the freely available community-contributed photos. We propose to conduct personalized travel recommendation by further considering specific user profiles or attributes (e.g., gender, age, race).
Instead of mining photo logs only, we argue to leverage the automatically detected people attributes in the photo contents. By information-theoretic measures, we will demonstrate that such people attributes are informative and effective for travel recommendation – especially providing a promising aspect for personalization. We effectively mine the demographics for different locations (or landmarks) and travel paths. A probabilistic Bayesian learning framework which further entails mobile recommendation on the spot is introduced. We experiment on ten million photos collected for 19 major worldwide cities. The experiments confirm that people attributes are promising and orthogonal to prior works using travel logs only and can further improve prior travel recommendation methods especially in difficult predictions by further leveraging user contexts in mobile devices. | en |
dc.description.provenance | Made available in DSpace on 2021-06-08T06:24:44Z (GMT). No. of bitstreams: 1 ntu-100-R98922061-1.pdf: 3179229 bytes, checksum: 3970639281e6a19290dc9d363a590051 (MD5) Previous issue date: 2011 | en |
dc.description.tableofcontents | 摘要 i
Abstract ii 1 Introduction 1 2 Related Work 5 3 Observations 7 3.1 Rich People Attributes in User-Contributed Photos 7 3.2 Correlation between Travel Patterns and People Attributes 8 4 System Overview 11 5 People Attribute Detection 13 5.1 Preprocessing 13 5.2 Mid-level Features 14 5.3 Ensemble Learning for Different Attributes 15 6 Photo Trip generation 16 6.1 Path Extraction 17 6.2 Destination Discovering and Route Mapping 17 6.3 Trip Attribute Pattern Mining 18 7 Tourist Recommendation Model 20 7.1 Bayesian Learning Model 21 7.2 Background Smoothing 22 8 Route Planning 24 9 Experiments 26 9. 1 Mobile Travel Recommendation 27 9.1.1 Impact of Background Smoothing 28 9.1.2 The Recommendation Performance 28 9.2 The Impact of People Attributes 29 9.3 Route Planning 31 10 Conclusions 33 Bibliography 34 | |
dc.language.iso | en | |
dc.title | 基於社群媒體照片之人物屬性建構個人化旅遊推薦系統 | zh_TW |
dc.title | Personalized Travel Recommendation by Mining People Attributes from Community-Contributed Photos | en |
dc.type | Thesis | |
dc.date.schoolyear | 99-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 林軒田(Hsuan-Tien Lin),賴尚宏(Shang-Hong Lai),黃俊翔(Chun-Hsiang Huang) | |
dc.subject.keyword | 個人化旅遊推薦,地理標記照片,旅遊路徑規劃,群眾外包,人物屬性, | zh_TW |
dc.subject.keyword | Personalized tourist recommendation,Geo-tagged photos,Route planning,Crowd-sourcing,People attribute, | en |
dc.relation.page | 36 | |
dc.rights.note | 未授權 | |
dc.date.accepted | 2011-08-03 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
顯示於系所單位: | 資訊工程學系 |
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