The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.
Dependency-Based Construction of Semantic Space Models
Abstract
Traditionally, vector-based semantic space models use word co-occurrence counts from large corpora to represent lexical meaning. In this article we present a novel framework for constructing semantic spaces that takes syntactic relations into account. We introduce a formalization for this class of models, which allows linguistic knowledge to guide the construction process. We evaluate our framework on a range of tasks relevant for cognitive science and natural language processing: semantic priming, synonymy detection, and word sense disambiguation. In all cases, our framework obtains results that are comparable or superior to the state of the art.
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A vector space model for automatic indexing
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Using Information Content to Evaluate Semantic Similarity in a Taxonomy
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Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy
Jiang, J. J., & Conrath, D. W. (1997) · arXiv (Cornell University) · doi:10.48550/arxiv.cmp-lg/9709008 · Cited by 2,743
Accurate methods for the statistics of surprise and coincidence
Dunning, T. E. (1993) · doi:10.5555/972450.972454 · Cited by 2,647
English Verb Classes and Alternations: A Preliminary Investigation
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Cited by
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Socher, R., Perelygin, A., Wu, J., Chuang, J., Manning, C. D., Ng, A., & Potts, C. (2013) · Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing · doi:10.18653/v1/d13-1170 · Cited by 6,878
Baroni, M., Dinu, G., & Kruszewski, G. (2014) · Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · doi:10.3115/v1/p14-1023 · Cited by 1,364
Improving Distributional Similarity with Lessons Learned from Word Embeddings
Levy, O., Goldberg, Y., & Dagan, I. (2015) · Transactions of the Association for Computational Linguistics · doi:10.1162/tacl_a_00134 · Cited by 1,308
Dependency-Based Word Embeddings
Levy, O., & Goldberg, Y. (2014) · Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) · doi:10.3115/v1/p14-2050 · Cited by 1,047
Zero-Shot Learning Through Cross-Modal Transfer
Socher, R., Ganjoo, M., Sridhar, H., Bastani, O., Manning, C. D., & Ng, A. Y. (2013) · arXiv · doi:10.48550/arxiv.1301.3666 · Cited by 997
Metadata
- Authors
- Padó, S., & Lapata, M.
- Venue
- Computational Linguistics
- Publisher
- MIT Press - Journals
- Published
- 2007-06
- Volume
- 33
- Issue
- 2
- Pages
- 161-199
- ISSN
- 0891-2017 (ISSN-L)
- 1530-9312
- OpenAlex
- W2005181355
- Cited by
- 695
- References
- 65
- FWCI
- 52.01
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
