2013 TextNowin2DAFrameworkforLexical
- (Biemann & Riedl, 2013) ⇒ Chris Biemann, and Martin Riedl. (2013). “Text: Now in 2D! A Framework for Lexical Expansion with Contextual Similarity.” In: J. Lang. Model., 1(1).
Subject Headings: Word Embedding System; JoBimText System.
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- Google Scholar: ~ 136 Citations.
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Abstract
A new metaphor of two-dimensional text for data-driven semantic modeling of natural language is proposed, which provides an entirely new angle on the representation of text: not only syntagmatic relations are annotated in the text, but also paradigmatic relations are made explicit by generating lexical expansions. We operationalize distributional similarity in a general framework for large corpora, and describe a new method to generate similar terms in context. Our evaluation shows that distributional similarity is able to produce high-quality lexical resources in an unsupervised and knowledge-free way, and that our highly scalable similarity measure yields better scores in a WordNet-based evaluation than previous measures for very large corpora. Evaluating on a lexical substitution task, we find that our contextualization method improves over a non-contextualized baseline across all parts of speech, and we show how the metaphor can be applied successfully to part-of-speech tagging. A number of ways to extend and improve the contextualization method within our framework are discussed. As opposed to comparable approaches, our framework defines a model of lexical expansions in context that can generate the expansions as opposed to ranking a given list, and thus does not require existing lexical-semantic resources.
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| Author | volume | Date Value | title | type | journal | titleUrl | doi | note | year | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2013 TextNowin2DAFrameworkforLexical | Chris Biemann Martin Riedl | Text: Now in 2D! A Framework for Lexical Expansion with Contextual Similarity |