Inferring Activities from Interactions with Objects
IEEE Pervasive Computing
Temporal management of RFID data
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Activity Recognition and Monitoring Using Multiple Sensors on Different Body Positions
BSN '06 Proceedings of the International Workshop on Wearable and Implantable Body Sensor Networks
A Pipelined Framework for Online Cleaning of Sensor Data Streams
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Adaptive cleaning for RFID data streams
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Data Management in the Worldwide Sensor Web
IEEE Pervasive Computing
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
A hybrid discriminative/generative approach for modeling human activities
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Achieving optimal data storage position in wireless sensor networks
Computer Communications
Spatio-temporal event detection using dynamic conditional random fields
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Abnormal activity recognition based on HDP-HMM models
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
The schema theory for semantic link network
Future Generation Computer Systems
LODE: Linking Open Descriptions of Events
ASWC '09 Proceedings of the 4th Asian Conference on The Semantic Web
A long-term evaluation of sensing modalities for activity recognition
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Structural analysis of the emerging event-web
Proceedings of the 19th international conference on World wide web
Towards physical mashups in the web of things
INSS'09 Proceedings of the 6th international conference on Networked sensing systems
An activity monitoring system for elderly care using generative and discriminative models
Personal and Ubiquitous Computing
Discovering Activities to Recognize and Track in a Smart Environment
IEEE Transactions on Knowledge and Data Engineering
Linked Data
A Pattern Mining Approach to Sensor-Based Human Activity Recognition
IEEE Transactions on Knowledge and Data Engineering
Recognizing Multiuser Activities Using Wireless Body Sensor Networks
IEEE Transactions on Mobile Computing
An Integrated Network and Data Management System for Heterogeneous WSNs
MASS '11 Proceedings of the 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems
A Knowledge-Driven Approach to Activity Recognition in Smart Homes
IEEE Transactions on Knowledge and Data Engineering
Transfer learning for activity recognition via sensor mapping
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Semantics for the Internet of Things: Early Progress and Back to the Future
International Journal on Semantic Web & Information Systems
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Extracting news blog hot topics based on the W2T Methodology
World Wide Web
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An exciting paradise of data is emerging into our daily life along with the development of the Web of Things. Nowadays, volumes of heterogeneous raw data are continuously generated and captured by trillions of smart devices like sensors, smart controls, readers and other monitoring devices, while various events occur in the physical world. It is hard for users including people and smart things to master valuable information hidden in the massive data, which is more useful and understandable than raw data for users to get the crucial points for problems-solving. Thus, how to automatically and actively extract the knowledge of events and their internal links from the big data is one key challenge for the future Web of Things. This paper proposes an effective approach to extract events and their internal links from large scale data leveraging predefined event schemas in the Web of Things, which starts with grasping the critical data for useful events by filtering data with well-defined event types in the schema. A case study in the context of smart campus is presented to show the application of proposed approach for the extraction of events and their internal semantic links.