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Instead of emphasizing the development of novel feature sets for machine learning, this study investigates the effect of various tag schemes on the recognition of the names of chemicals and drugs by using conditional random fields.
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In this paper, we present and evaluated CTF, a novel integrative method to predict transcription factor binding sties (TFBSs) by combining various features using conditional random field as the underlying framework.
For protein-protein interaction, Morihiro Hayashida et al. proposed novel methods using conditional random fields for predicting protein-protein interactions by utilizing the fact that mutual information between residues at interacting sites can be higher than that at non-interacting sites.
The system introduced by Lu et al. [135] identified players in broadcast sports videos using conditional random fields and achieved a player recognition accuracy up to 85% on unlabeled NBA basketball clips.
Furthermore, spatial properties of skin regions were analyzed using conditional random fields [56] and cellular automata [49].
Chung [ 8] extended this work to I and O elements using Conditional Random Fields (CRF).
Specifically, we modelled the data using conditional random fields (CRFs) (49).
We propose novel methods using conditional random fields for predicting protein-protein interactions.
We propose novel methods using conditional random fields with and without mutual information between domains.
We have recently tested a module using Conditional Random Fields (CRF) for recognizing the toponyms.
BANNER is a trainable system, using conditional random fields (Lafferty et al., 2001) and a rich feature set approach.
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