edu.cmu.minorthird.ui
Class Recommended.VPSMMLearner
java.lang.Object
edu.cmu.minorthird.text.learn.AnnotatorLearner
edu.cmu.minorthird.text.learn.ConditionalSemiMarkovModel.CSMMLearner
edu.cmu.minorthird.ui.Recommended.VPSMMLearner
- Enclosing class:
- Recommended
public static class Recommended.VPSMMLearner
- extends ConditionalSemiMarkovModel.CSMMLearner
Uses the voted perceptron algorithm to learn the parameters for a
hidden semi-Markov model (SMM).
This is a somewhat more expensive version of the VPHMMLearner,
which allows features to describe properties of multi-token
spans, rather than only properties of single tokens. This
implements the training algorithm described in the initial
draft of Cohen & Saragi's KDD paper. This implementation is less
memory-intensive than the VPSMMLearner2 package below, but
slower, since the feature-extraction step is iterated many times.
Reference: William W. Cohen and Sunita Sarawagi, Exploiting
Dictionaries in Named Entity Extraction: Combining Semi-Markov
Extraction Processes and Data Integration Methods,
Proceedings of the Tenth ACM SIGKDD International Conference on
Knowledge Discovery and Data Mining (KDD-2004).
Methods inherited from class edu.cmu.minorthird.text.learn.ConditionalSemiMarkovModel.CSMMLearner |
getAnnotationType, getAnnotator, getEpochs, getLearner, getMaxSegmentSize, getSpanFeatureExtractor, hasNextQuery, nextQuery, reset, setAnnotationType, setAnswer, setDocumentPool, setEpochs, setLearner, setMaxSegmentSize, setSpanFeatureExtractor |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Recommended.VPSMMLearner
public Recommended.VPSMMLearner()
- Extracted entities must be of length 4 or less.
Recommended.VPSMMLearner
public Recommended.VPSMMLearner(int maxLength)