UDM 2005: Tokyo, Japan

2005 International Workshop on Ubiquitous Data Management (UDM 2005), 4 April 2005, Tokyo, Japan. IEEE Computer Society 2005, ISBN 0-7695-2411-7 BibTeX

Cover

Title Page.
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Copyright.
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Introduction

Preface.
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Message from the Program Committee Chair.
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Organizing Committee.
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Program Committee.
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Session 1: Keynote Talks

Erich J. Neuhold, Claudia Niederée, Ingo Frommholz, Avare Stewart, Bhaskar Mehta:
The Role of Context for Information Mediation. 3-5
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Stefano Spaccapietra, Lina Al-Jadir, Shijun Yu:
Somebody, Sometime, Somewhere, Something. 6-16
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Session 2: Context Computing

Arthur H. van Bunningen, Ling Feng, Peter M. G. Apers:
Context for Ubiquitous Data Management. 17-24
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Jeong Hee Hwang, Myung-Jin Lee, Oh-Cheon Kwon, Keun Ho Ryu:
Context-based Preference Analysis Method in Ubiquitous Commerce. 25-32
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Suan Khai Chong, Seng Wai Loke, Shonali Krishnaswamy:
Wireless Sensor Networks: From Data to Context to Energy Saving. 33-42
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Session 3: Invited Talks

Hui Lei:
Context Awareness: a Practitioner';s Perspective. 43-52
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Gareth J. F. Jones:
Challenges and Opportunities of Context-Aware Information Access. 53-62
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Session 4: Architecture for Ubiquitous Data Management

Larry Kerschberg, Hanjo Jeong:
Ubiquitous Data Management in Knowledge Sifter via Data-DNA. 63-70
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Hideyuki Fujita, Masatoshi Arikawa:
A Ubiquitous Photo Mapping Considering Users' Lines of Sight. 71-77
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Cheng-Ru Young, Ge-Ming Chiu:
An Efficient Protocol for Disseminating Consistent Data in Broadcast Environments. 78-85
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Yasue Kishino, Tsutomu Terada, Masahiko Tsukamoto, Shojiro Nishio:
A Ubiquitous Computing Environment Composed by Cooperation between Visual Markers and Event-Driven Compact Devices. 86-96
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Session 5: Data Mining for Ubiquitious Data

Kimio Kuramitsu:
Finding Periodic Outliers over a Monogenetic Event Stream. 97-104
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Vincent Shin-Mu Tseng, Kawuu Weicheng Lin:
Mining Temporal Moving Patterns in Object Tracking Sensor Networks. 105-112
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Rajanish Dass, Ambuj Mahanti:
Implementing BDFS(b) with Diff-Sets for Real-Time Frequent Pattern Mining in Dense Datasets - First Findings. 113-120
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