SoHyun Park


Classifying Out-of-vocabulary Terms in a Domain-Specific Social Media Corpus
SoHyun Park | Afsaneh Fazly | Annie Lee | Brandon Seibel | Wenjie Zi | 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 | Waseem Gharbieh | SoHyun Park | Paul Cook
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)