Sciweavers

616 search results - page 1 / 124
» Hierarchical Hidden Markov Models for Information Extraction
Sort
View
IJCAI
2003
14 years 6 days ago
Hierarchical Hidden Markov Models for Information Extraction
Information extraction can be defined as the task of automatically extracting instances of specified classes or relations from text. We consider the case of using machine learni...
Marios Skounakis, Mark Craven, Soumya Ray
IJCAI
2001
14 years 7 days ago
Representing Sentence Structure in Hidden Markov Models for Information Extraction
We study the application of Hidden Markov Models (HMMs) to learning information extractors for
Soumya Ray, Mark Craven
MM
2005
ACM
140views Multimedia» more  MM 2005»
14 years 4 months ago
Topic transition detection using hierarchical hidden Markov and semi-Markov models
In this paper we introduce a probabilistic framework to exploit hierarchy, structure sharing and duration information for topic transition detection in videos. Our probabilistic d...
Dinh Q. Phung, Thi V. Duong, Svetha Venkatesh, Hun...
ICIP
2004
IEEE
15 years 13 days ago
Automatically learning structural units in educational videos with the hierarchical hidden markov models
In this paper we present a coherent approach using the hierarchical HMM with shared structures to extract the structural units that form the building blocks of an education/traini...
Dinh Q. Phung, Svetha Venkatesh, Hung Hai Bui
ACL
2006
14 years 7 days ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone