Cogprints

A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations

Turney, Peter D. (2008) A Uniform Approach to Analogies, Synonyms, Antonyms, and Associations. [Conference Paper]

Full text available as:

[img]
Preview
PDF - Accepted Version
67Kb

Abstract

Recognizing analogies, synonyms, antonyms, and associations appear to be four distinct tasks, requiring distinct NLP algorithms. In the past, the four tasks have been treated independently, using a wide variety of algorithms. These four semantic classes, however, are a tiny sample of the full range of semantic phenomena, and we cannot afford to create ad hoc algorithms for each semantic phenomenon; we need to seek a unified approach. We propose to subsume a broad range of phenomena under analogies. To limit the scope of this paper, we restrict our attention to the subsumption of synonyms, antonyms, and associations. We introduce a supervised corpus-based machine learning algorithm for classifying analogous word pairs, and we show that it can solve multiple-choice SAT analogy questions, TOEFL synonym questions, ESL synonym-antonym questions, and similar-associated-both questions from cognitive psychology.

Item Type:Conference Paper
Additional Information:NRC 50398
Keywords:analogies, synonyms, antonyms, associations, distributional hypothesis, semantics
Subjects:Computer Science > Language
Linguistics > Computational Linguistics
Linguistics > Semantics
Computer Science > Machine Learning
Computer Science > Artificial Intelligence
ID Code:6181
Deposited By:Turney, Peter
Deposited On:31 Aug 2008 13:24
Last Modified:11 Mar 2011 08:57

References in Article

Select the SEEK icon to attempt to find the referenced article. If it does not appear to be in cogprints you will be forwarded to the paracite service. Poorly formated references will probably not work.

Breiman, Leo. 1996. Bagging predictors. Machine Learning, 24(2):123–140.

Buettcher, Stefan and Charles Clarke. 2005. Efficiency vs. effectiveness in terabyte-scale information retrieval. In Proceedings of the 14th Text REtrieval Conference (TREC 2005), Gaithersburg, MD.

Chiarello, Christine, Curt Burgess, Lorie Richards, and Alma Pollock. 1990. Semantic and associative priming in the cerebral hemispheres: Some words do, some words don’t ... sometimes, some places. Brain and Language, 38:75–104.

Falkenhainer, Brian, Kenneth D. Forbus, and Dedre Gentner. 1989. The structure-mapping engine: Algorithm and examples. Artificial Intelligence, 41(1):1–63.

Fellbaum, Christiane, editor. 1998. WordNet: An Electronic Lexical Database. MIT Press.

Girju, Roxana, Preslav Nakov, Vivi Nastase, Stan Szpakowicz, Peter Turney, and Deniz Yuret. 2007. Semeval-2007 task 04: Classification of semantic relations between nominals. In SemEval 2007, pages 13–18, Prague, Czech Republic.

Hirst, Graeme and David St-Onge. 1998. Lexical chains as representations of context for the detection and correction of malapropisms. In Fellbaum, Christiane, editor, WordNet: An Electronic Lexical Database, pages 305–332. MIT Press.

Hofstadter, Douglas. 2007. I Am a Srange Loop. Basic Books.

Jiang, Jay J. and David W. Conrath. 1997. Semantic similarity based on corpus statistics and lexical taxonomy. In ROCLING X, pages 19–33, Tapei, Taiwan.

Landauer, Thomas K. and Susan T. Dumais. 1997. A solution to Plato’s problem: The latent semantic analysis theory of the acquisition, induction, and representation of knowledge. Psychological Review, 104(2):211–240.

Lepage, Yves and Etienne Denoual. 2005. Purest ever example-based machine translation: Detailed presentation and assessment. Machine Translation, 19(3):251–282.

Lepage, Yves. 1998. Solving analogies on words: An algorithm. In Proceedings of the 36th Annual Conference of the Association for Computational Linguistics, pages 728–735.

Lesk, Michael E. 1969. Word-word associations in document retrieval systems. American Documentation, 20(1):27–38.

Lin, Dekang, Shaojun Zhao, Lijuan Qin, and Ming Zhou. 2003. Identifying synonyms among distributionally similar words. In IJCAI-03, pages 1492–1493.

Lund, Kevin, Curt Burgess, and Ruth Ann Atchley. 1995. Semantic and associative priming in high-dimensional semantic space. In Proceedings of the 17th Annual Conference of the Cognitive Science Society, pages 660–665.

Minnen, Guido, John Carroll, and Darren Pearce. 2001. Applied morphological processing of English. Natural Language Engineering, 7(3):207–223.

Minsky, Marvin. 1986. The Society of Mind. Simon & Schuster, New York, NY.

Nastase, Vivi and Stan Szpakowicz. 2003. Exploring noun-modifier semantic relations. In Fifth International Workshop on Computational Semantics (IWCS-5), pages 285–301, Tilburg, The Netherlands.

Platt, John C. 1998. Fast training of support vector machines using sequential minimal optimization. In Advances in Kernel Methods: Support Vector Learning, pages 185–208. MIT Press Cambridge, MA, USA.

Reitman, Walter R. 1965. Cognition and Thought: An Information Processing Approach. John Wiley and Sons, New York, NY.

Resnik, Philip. 1995. Using information content to evaluate semantic similarity in a taxonomy. In IJCAI-95, pages 448–453, San Mateo, CA. Morgan Kaufmann.

Rosario, Barbara and Marti Hearst. 2001. Classifying the semantic relations in noun-compounds via a domain-specific lexical hierarchy. In EMNLP-01, pages 82–90.

Turney, Peter D. and Michael L. Littman. 2005. Corpus-based learning of analogies and semantic relations. Machine Learning, 60(1–3):251–278.

Turney, Peter D., Michael L. Littman, Jeffrey Bigham, and Victor Shnayder. 2003. Combining independent modules to solve multiple-choice synonym and analogy problems. In RANLP-03, pages 482–489, Borovets, Bulgaria.

Turney, Peter D. 2001. Mining the Web for synonyms: PMI-IR versus LSA on TOEFL. In Proceedings of the Twelfth European Conference on Machine Learning, pages 491–502, Berlin. Springer.

Turney, Peter D. 2006. Similarity of semantic relations. Computational Linguistics, 32(3):379–416.

Veale, Tony. 2004. WordNet sits the SAT: A knowledge-based approach to lexical analogy. In Proceedings of the 16th European Conference on Artificial Intelligence (ECAI 2004), pages 606–612, Valencia, Spain.

Witten, Ian H. and Eibe Frank. 1999. Data Mining: Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann, San Francisco.

Metadata

Repository Staff Only: item control page