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» Hierarchical Hidden Markov Models for Information Extraction
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CVPR
2005
IEEE
16 years 1 months ago
Activity Recognition and Abnormality Detection with the Switching Hidden Semi-Markov Model
This paper addresses the problem of learning and recognizing human activities of daily living (ADL), which is an important research issue in building a pervasive and smart environ...
Thi V. Duong, Hung Hai Bui, Dinh Q. Phung, Svetha ...
CIVR
2009
Springer
257views Image Analysis» more  CIVR 2009»
15 years 6 months ago
Trajectory-based handball video understanding
This paper presents a content-based approach for understanding handball videos. Tracked players are characterized by their 2D trajectories in the court plane. The trajectories and...
Alexandre Hervieu, Patrick Bouthemy, Jean-Pierre L...
SIGIR
2003
ACM
15 years 5 months ago
Table extraction using conditional random fields
The ability to find tables and extract information from them is a necessary component of data mining, question answering, and other information retrieval tasks. Documents often c...
David Pinto, Andrew McCallum, Xing Wei, W. Bruce C...
NAACL
2010
14 years 9 months ago
Improved Extraction Assessment through Better Language Models
A variety of information extraction techniques rely on the fact that instances of the same relation are "distributionally similar," in that they tend to appear in simila...
Arun Ahuja, Doug Downey
JMLR
2008
159views more  JMLR 2008»
14 years 11 months ago
Dynamic Hierarchical Markov Random Fields for Integrated Web Data Extraction
Existing template-independent web data extraction approaches adopt highly ineffective decoupled strategies--attempting to do data record detection and attribute labeling in two se...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen