90 search results - page 1 / 18 » Maximum Entropy Markov Models for Information Extraction and... |
ICML
2000
IEEE
14 years 5 months ago
2000
IEEE
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
ISMIR
2005
Springer
13 years 9 months ago
2005
Springer
Music information retrieval is characterized by a number of various user information needs. Systems are being developed that allow searchers to find melodies, rhythms, genres, an...
CIKM
2005
Springer
13 years 9 months ago
2005
Springer
This paper describes a framework for defining domain specific Feature Functions in a user friendly form to be used in a Maximum Entropy Markov Model (MEMM) for the Named Entity Re...
IJCNLP
2005
Springer
13 years 9 months ago
2005
Springer
This paper proposes a chunking strategy to detect unknown words in Chinese word segmentation. First, a raw sentence is pre-segmented into a sequence of word atoms 1 using a maximum...
NLPRS
2001
Springer
13 years 8 months ago
2001
Springer
We describe a new tagging model where the states of a hidden Markov model (HMM) estimated by unsupervised learning are incorporated as the features in a maximum entropy model. Our...