SoHyun Park
2016
Classifying Out-of-vocabulary Terms in a Domain-Specific Social Media Corpus
SoHyun Park
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Afsaneh Fazly
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Annie Lee
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Brandon Seibel
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Wenjie Zi
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Paul Cook
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
In this paper we consider the problem of out-of-vocabulary term classification in web forum text from the automotive domain. We develop a set of nine domain- and application-specific categories for out-of-vocabulary terms. We then propose a supervised approach to classify out-of-vocabulary terms according to these categories, drawing on features based on word embeddings, and linguistic knowledge of common properties of out-of-vocabulary terms. We show that the features based on word embeddings are particularly informative for this task. The categories that we predict could serve as a preliminary, automatically-generated source of lexical knowledge about out-of-vocabulary terms. Furthermore, we show that this approach can be adapted to give a semi-automated method for identifying out-of-vocabulary terms of a particular category, automotive named entities, that is of particular interest to us.
UNBNLP at SemEval-2016 Task 1: Semantic Textual Similarity: A Unified Framework for Semantic Processing and Evaluation
Milton King
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Waseem Gharbieh
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SoHyun Park
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Paul Cook
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)
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Co-authors
- Paul Cook 2
- Afsaneh Fazly 1
- Annie Lee 1
- Brandon Seibel 1
- Wenjie Zi 1
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