First International Workshop on Knowledge
Discovery from Sensor Data (Sensor-KDD '07)

 

To be held in conjunction with

Sensor-KDD
'07 Workshop
 
August 12, 2007
San Jose, California, USA

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Program Schedule


Date: August 12, 2007

Duration: Full-day

Final Workshop Program:

09:00am - 09:15am

Full Paper 1 Presentation:
Requirements for Clustering Streaming Sensors by Rodrigues et al.

09:15am - 09:30am Full Paper 2 Presentation:
Fusion of Vision Inertia Data for Automatic Geo-referencing by Randeniya et al.
09:30am - 10:00am Poster Papers Presentation @ 5 minutes each:
1) Mixtures of Probabilistic Principal Component Analyzers for Anomaly Detection
by Fang and Ganguly
2) Correlation-based Feature Partitioning for Rare Event Detection in Wireless Sensor Networks by Asur and Parthasarathy

3) Unsupervised and supervised compression with PCA in Wireless Sensor Networks by Le Borgne and Bontempi
4) Trade-offs in the use of Bayesian Filtering for Sensor Fusion by Gershman et al.
5) Prediction of Missing Events in Sensor Data Streams using Kalman Filters by Vijayakumar and Plale
6) Mining Sensor Data in Smart Environment for Temporal Activity Prediction by Jakkula and Cook
10:00am - 10:30am Coffee Break & Poster Viewing Session I
10:30am - 10:45am 2nd Best Student Paper Presentation:
Anomaly Detection in Transportation Corridors using Manifold Embedding by Agovic et al.
10:45am - 11:00am 1st Best Student Paper Presentation:
Spatio-Temporal Analysis on FEMA Situation Updates with Automated Information Extraction by Pan et al.
11:00am - 11:30am Invited Speaker 1 Talk:
Peer-to-Peer Distributed Data Stream Mining and Monitoring by Hillol Kargupta, University of Maryland
11:30am - 12:00Noon Invited Speaker 2 Talk:
New Frontiers and Opportunities in Sensor-driven Knowledge Discovery by Brian Worley, Oak Ridge National Laboratory
12:00Noon - 02:00pm Lunch (On your own)
02:00pm - 02:30pm Invited Speaker 3 Talk:
A Probabilistic Framework for Mining Distributed Sensory Data under Data Sharing Constraints by Joydeep Ghosh, University of Texas
02:30pm - 03:00pm Invited Speaker 4 Talk:
A General Framework for Mining Massive Data Streams by Pedro Domingos, University of Washington
03:00pm - 03:30pm Coffee Break & Poster Viewing Session II
03:30pm - 04:00pm 2nd Best Paper Presentation:
Electricity Load Forecast using Data Streams Techniques by Gama
and Rodrigues
04:00pm - 04:30pm 1st Best Paper Presentation:
TAG: A Framework for the Discovery of Spatio-Temporal Patterns in Sensor Data by George, Kang, and Shekhar
04:30pm - 05:00pm Panel Discussion

 

 
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