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ORCIDUDM 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
Cover
- Title Page.
- Copyright.
Introduction
- Preface.
- Message from the Program Committee Chair.
- Organizing Committee.
- Program Committee.
Session 1: Keynote Talks
- Erich J. Neuhold, Claudia Niederée
, Ingo Frommholz, Avare Stewart, Bhaskar Mehta:
The Role of Context for Information Mediation. 3-5 - Stefano Spaccapietra, Lina Al-Jadir, Shijun Yu:
Somebody, Sometime, Somewhere, Something. 6-16
Session 2: Context Computing
- Arthur H. van Bunningen, Ling Feng, Peter M. G. Apers:
Context for Ubiquitous Data Management. 17-24 - Jeong Hee Hwang, Myung-Jin Lee, Oh-Cheon Kwon, Keun Ho Ryu:
Context-based Preference Analysis Method in Ubiquitous Commerce. 25-32 - Suan Khai Chong, Seng Wai Loke, Shonali Krishnaswamy:
Wireless Sensor Networks: From Data to Context to Energy Saving. 33-42
Session 3: Invited Talks
- Hui Lei:
Context Awareness: a Practitioner's Perspective. 43-52 - Gareth J. F. Jones:
Challenges and Opportunities of Context-Aware Information Access. 53-62
Session 4: Architecture for Ubiquitous Data Management
- Larry Kerschberg, Hanjo Jeong:
Ubiquitous Data Management in Knowledge Sifter via Data-DNA. 63-70 - Hideyuki Fujita, Masatoshi Arikawa:
A Ubiquitous Photo Mapping Considering Users' Lines of Sight. 71-77 - Cheng-Ru Young, Ge-Ming Chiu:
An Efficient Protocol for Disseminating Consistent Data in Broadcast Environments. 78-85 - 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
Session 5: Data Mining for Ubiquitious Data
- Kimio Kuramitsu:
Finding Periodic Outliers over a Monogenetic Event Stream. 97-104 - Vincent Shin-Mu Tseng, Kawuu Weicheng Lin:
Mining Temporal Moving Patterns in Object Tracking Sensor Networks. 105-112 - 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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