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 10 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 10 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 10 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 9 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...