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2009
ACM
16 years 7 months ago
A methodology for extracting temporal properties from sensor network data streams
The extraction of temporal characteristics from sensor data streams can reveal important properties about the sensed events. Knowledge of temporal characteristics in applications ...
Dimitrios Lymberopoulos, Athanasios Bamis, Andreas...
KDD
2008
ACM
115views Data Mining» more  KDD 2008»
16 years 7 months ago
SPIRAL: efficient and exact model identification for hidden Markov models
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...
Yasuhiro Fujiwara, Yasushi Sakurai, Masashi Yamamu...
KDD
2006
ACM
162views Data Mining» more  KDD 2006»
16 years 7 months ago
Simultaneous record detection and attribute labeling in web data extraction
Recent work has shown the feasibility and promise of templateindependent Web data extraction. However, existing approaches use decoupled strategies ? attempting to do data record ...
Jun Zhu, Zaiqing Nie, Ji-Rong Wen, Bo Zhang, Wei-Y...
KDD
2004
ACM
151views Data Mining» more  KDD 2004»
16 years 7 months ago
Feature selection in scientific applications
Numerous applications of data mining to scientific data involve the induction of a classification model. In many cases, the collection of data is not performed with this task in m...
Erick Cantú-Paz, Shawn Newsam, Chandrika Ka...
KDD
2004
ACM
170views Data Mining» more  KDD 2004»
16 years 7 months ago
Why collective inference improves relational classification
Procedures for collective inference make simultaneous statistical judgments about the same variables for a set of related data instances. For example, collective inference could b...
David Jensen, Jennifer Neville, Brian Gallagher
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