Examples of edu.ucla.sspace.wordsi.DependencyContextGenerator

• edu.ucla.sspace.wordsi.DependencyContextGenerator
  An interface for generating context vectors from raw unparsed text. A context vector can be generated from a sliding window of text. {@link ContextGenerator}s are a subcomponent of {@link ContextExtractor}s. As a {@link ContextExtractor} examines text and finds a word which is beingrepresented in the {@link Wordsi} space, it will call the {@link ContextGenerator} and pass the created context vector to a {@link Wordsi}implementation.

  {@link ContextGenerator}s are recomended to be made serializable. They will serve as the core representation method of {@link Wordsi} implementations andcan thus be re-used in multiple evaluations. For example, after training a {@link Wordsi} model, it may need to be evaluated in a psuedo-worddisambiguation task or a SemEval task. In both cases, the feature space must remain the same turing training and evaluation.

  For evaluation purposes, an added option is available: a read only mode. When in read only mode, {@link ContextGenerator}s should not create any new features. If some co-occurring term does not exist in the feature space, it should be left out of the context vector, only feature which already exist in the space should contribute to the context vector. In standard mode, the generator is permitted to decided which words should serve as features using any method. @author Keith Stevens

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