Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgments

@inproceedings{Cramer2012ExploringRF,
  title={Exploring Resources for Lexical Chaining: A Comparison of Automated Semantic Relatedness Measures and Human Judgments},
  author={Irene M. Cramer and Tonio Wandmacher and Ulli Waltinger},
  booktitle={Modeling, Learning, and Processing of Text Technological Data Structures},
  year={2012}
}
In the past decade various semantic relatedness, similarity, and distance measures have been proposed which play a crucial role in many NLP-applications. Researchers compete for better algorithms (and resources to base the algorithms on), and often only few percentage points seem to suffice in order to prove a new measure (or resource) more accurate than an older one. However, it is still unclear which of them performs best under what conditions. In this work we therefore present a study… CONTINUE READING
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