TOEFL Synonym Questions (State of the art) - Revision history

Doboandris at 00:32, 16 September 2019

2019-09-16T00:32:59Z

← Older revision		Revision as of 00:32, 16 September 2019
Line 293:		Line 293:
	Bullinaria, J.A., and Levy, J.P. (2012). [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.228.9582&rep=rep1&type=pdf Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD]. ''Behavior Research Methods'', 44(3):890-907.		Bullinaria, J.A., and Levy, J.P. (2012). [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.228.9582&rep=rep1&type=pdf Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD]. ''Behavior Research Methods'', 44(3):890-907.

	Dobó, A. (2019). [http://doktori.bibl.u-szeged.hu/10120/1/AndrasDoboThesis2019.pdf A comprehensive analysis of the parameters in the creation and comparison of feature vectors in distributional semantic models for multiple languages]. University of Szeged.		Dobó, A. (2019). [http://doktori.bibl.u-szeged.hu/10120/1/AndrasDoboThesis2019.pdf A comprehensive analysis of the parameters in the creation and comparison of feature vectors in distributional semantic models for multiple languages]. University of Szeged. [https://github.com/doboandras/dsm-parameter-analysis GitHub repository]

	Dobó, A., and Csirik, J. (2013). [http://link.springer.com/chapter/10.1007/978-3-642-35843-2_42 Computing semantic similarity using large static corpora]. In: van Emde Boas, P. et al. (eds.) ''SOFSEM 2013: Theory and Practice of Computer Science. LNCS, Vol. 7741''. Springer-Verlag, Berlin Heidelberg, pp. 491-502		Dobó, A., and Csirik, J. (2013). [http://link.springer.com/chapter/10.1007/978-3-642-35843-2_42 Computing semantic similarity using large static corpora]. In: van Emde Boas, P. et al. (eds.) ''SOFSEM 2013: Theory and Practice of Computer Science. LNCS, Vol. 7741''. Springer-Verlag, Berlin Heidelberg, pp. 491-502

Doboandris at 22:53, 12 August 2019

2019-08-12T22:53:19Z

← Older revision		Revision as of 22:53, 12 August 2019
Line 319:		Line 319:
	Pado, S., and Lapata, M. (2007). [http://www.nlpado.de/~sebastian/pub/papers/cl07_pado.pdf Dependency-based construction of semantic space models]. ''Computational Linguistics'', 33(2), 161-199.		Pado, S., and Lapata, M. (2007). [http://www.nlpado.de/~sebastian/pub/papers/cl07_pado.pdf Dependency-based construction of semantic space models]. ''Computational Linguistics'', 33(2), 161-199.

	Pennington, J., Socher, R., and Manning, C. (2014). [https://www.aclweb.org/anthology/D14-1162 Glove: Global vectors for word representation. ''EMNLP 2014'', pp. 1532-1543.		Pennington, J., Socher, R., and Manning, C. (2014). [https://www.aclweb.org/anthology/D14-1162 Glove: Global vectors for word representation]. ''EMNLP 2014'', pp. 1532-1543.

	Pilehvar, M.T., Jurgens D., and Navigli R. (2013). [http://wwwusers.di.uniroma1.it/~navigli/pubs/ACL_2013_Pilehvar_Jurgens_Navigli.pdf Align, disambiguate and walk: A unified approach for measuring semantic similarity]. ''Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013),'' Sofia, Bulgaria.		Pilehvar, M.T., Jurgens D., and Navigli R. (2013). [http://wwwusers.di.uniroma1.it/~navigli/pubs/ACL_2013_Pilehvar_Jurgens_Navigli.pdf Align, disambiguate and walk: A unified approach for measuring semantic similarity]. ''Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013),'' Sofia, Bulgaria.

Doboandris at 21:39, 12 August 2019

2019-08-12T21:39:57Z

@@ Line 139: / Line 139: @@
 | 78.75%
 | 68.17–87.11%
 |-
 | PMI-IR
@@ Line 151: / Line 158: @@
 | Higgins (2005)
 | Web-based
 | 81.25%
 | 70.97–89.11%
@@ Line 182: / Line 196: @@
 | 78.21-93.84%
 |-
-| DC-best
+| DC13
 | Dobó and Csirik (2013)
 | Dobó and Csirik (2013)
@@ Line 188: / Line 202: @@
 | 88.75%
 | 79.72-94.72%
 |-
 | LSA
@@ Line 216: / Line 237: @@
 | 97.50%
 | 91.26–99.70%
 |-
 | PCCP
@@ Line 257: / Line 292: @@
 Bullinaria, J.A., and Levy, J.P. (2012). [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.228.9582&rep=rep1&type=pdf Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD]. ''Behavior Research Methods'',  44(3):890-907.
 Dobó, A., and Csirik, J. (2013). [http://link.springer.com/chapter/10.1007/978-3-642-35843-2_42 Computing semantic similarity using large static corpora]. In: van Emde Boas, P. et al. (eds.) ''SOFSEM 2013: Theory and Practice of Computer Science. LNCS, Vol. 7741''. Springer-Verlag, Berlin Heidelberg, pp. 491-502
@@ Line 281: / Line 318: @@
 Pado, S., and Lapata, M. (2007). [http://www.nlpado.de/~sebastian/pub/papers/cl07_pado.pdf Dependency-based construction of semantic space models]. ''Computational Linguistics'', 33(2), 161-199.
 Pilehvar, M.T., Jurgens D., and Navigli R. (2013). [http://wwwusers.di.uniroma1.it/~navigli/pubs/ACL_2013_Pilehvar_Jurgens_Navigli.pdf Align, disambiguate and walk: A unified approach for measuring semantic similarity]. ''Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013),'' Sofia, Bulgaria.
@@ Line 289: / Line 328: @@
 Ruiz-Casado, M., Alfonseca, E. and Castells, P. (2005) [http://alfonseca.org/pubs/2005-ranlp1.pdf Using context-window overlapping in Synonym Discovery and Ontology Extension]. ''Proceedings of the International Conference Recent Advances in Natural Language Processing (RANLP-2005)'', Borovets, Bulgaria.
 Terra, E., and Clarke, C.L.A. (2003). [http://acl.ldc.upenn.edu/N/N03/N03-1032.pdf Frequency estimates for statistical word similarity measures]. ''Proceedings of the Human Language Technology and North American Chapter of Association of Computational Linguistics Conference 2003 (HLT/NAACL 2003)'', pp. 244–251.

Pdturney at 14:44, 4 April 2017

2017-04-04T14:44:54Z

← Older revision		Revision as of 14:44, 4 April 2017
Line 1:		Line 1:
			* '''the TOEFL questions are available on request by contacting [http://lsa.colorado.edu/mail_sub.html LSA Support at CU Boulder]''', the people who manage the [http://lsa.colorado.edu/ LSA web site at Colorado]
	* TOEFL = Test of English as a Foreign Language		* TOEFL = Test of English as a Foreign Language
	* 80 multiple-choice synonym questions; 4 choices per question		* 80 multiple-choice synonym questions; 4 choices per question
	* the TOEFL questions are available on request by contacting [http://lsa.colorado.edu/mail_sub.html LSA Support at CU Boulder], the people who manage the [http://lsa.colorado.edu/ LSA web site at Colorado]
	* introduced in Landauer and Dumais (1997) as a way of evaluating algorithms for measuring degree of similarity between words		* introduced in Landauer and Dumais (1997) as a way of evaluating algorithms for measuring degree of similarity between words
	* subsequently used by many other researchers		* subsequently used by many other researchers

Pdturney: /* Table of results */

2015-10-29T22:10:43Z

Table of results

← Older revision		Revision as of 22:10, 29 October 2015
Line 182:		Line 182:
	\| 78.21-93.84%		\| 78.21-93.84%
	\|-		\|-
	\| ~~bnc~~-~~parsed-num-cos-loglh+enwiki-parsed-num-cos-pmi~~		\| DC-best
	\| Dobó and Csirik (2013)		\| Dobó and Csirik (2013)
	\| Dobó and Csirik (2013)		\| Dobó and Csirik (2013)

Doboandris at 20:48, 29 October 2015

2015-10-29T20:48:39Z

@@ Line 144: / Line 144: @@
 | Terra and Clarke (2003)
 | Corpus-based
 | 81.25%
 | 70.97–89.11%
@@ Line 167: / Line 174: @@
 | 86.25%
 | 76.73-92.93%
 |-
 | LSA
@@ Line 236: / Line 257: @@
 Bullinaria, J.A., and Levy, J.P. (2012). [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.228.9582&rep=rep1&type=pdf Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD]. ''Behavior Research Methods'',  44(3):890-907.
 Lushan Han. (2014). [http://ebiquity.umbc.edu/paper/html/id/658/Schema-Free-Querying-of-Semantic-Data Schema Free Querying of Semantic Data], Ph.D. dissertation, University of Maryland, Baltimore County, Baltimore, MD USA.
 Hirst, G., and St-Onge, D. (1998). [http://mirror.eacoss.org/documentation/ITLibrary/IRIS/Data/1997/Hirst/Lexical/1997-Hirst-Lexical.pdf Lexical chains as representation of context for the detection and correction of malapropisms]. In C. Fellbaum (ed.), ''WordNet: An Electronic Lexical Database''. Cambridge: MIT Press, 305-332.
@@ Line 266: / Line 291: @@
 Terra, E., and Clarke, C.L.A. (2003). [http://acl.ldc.upenn.edu/N/N03/N03-1032.pdf Frequency estimates for statistical word similarity measures]. ''Proceedings of the Human Language Technology and North American Chapter of Association of Computational Linguistics Conference 2003 (HLT/NAACL 2003)'', pp. 244–251.
 Turney, P.D. (2001). [http://arxiv.org/abs/cs.LG/0212033 Mining the Web for synonyms: PMI-IR versus LSA on TOEFL]. ''Proceedings of the Twelfth European Conference on Machine Learning (ECML-2001)'', Freiburg, Germany, pp. 491-502.

Pdturney at 17:23, 28 June 2015

2015-06-28T17:23:09Z

← Older revision		Revision as of 17:23, 28 June 2015
Line 275:		Line 275:

	[[Category:State of the art]]		[[Category:State of the art]]
			[[Category:Similarity]]

Finin: /* References */

2014-11-09T21:48:45Z

References

← Older revision		Revision as of 21:48, 9 November 2014
Line 236:		Line 236:

	Bullinaria, J.A., and Levy, J.P. (2012). [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.228.9582&rep=rep1&type=pdf Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD]. ''Behavior Research Methods'', 44(3):890-907.		Bullinaria, J.A., and Levy, J.P. (2012). [http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.228.9582&rep=rep1&type=pdf Extracting semantic representations from word co-occurrence statistics: stop-lists, stemming, and SVD]. ''Behavior Research Methods'', 44(3):890-907.

			Lushan Han. (2014). [http://ebiquity.umbc.edu/paper/html/id/658/Schema-Free-Querying-of-Semantic-Data Schema Free Querying of Semantic Data], Ph.D. dissertation, University of Maryland, Baltimore County, Baltimore, MD USA.

	Hirst, G., and St-Onge, D. (1998). [http://mirror.eacoss.org/documentation/ITLibrary/IRIS/Data/1997/Hirst/Lexical/1997-Hirst-Lexical.pdf Lexical chains as representation of context for the detection and correction of malapropisms]. In C. Fellbaum (ed.), ''WordNet: An Electronic Lexical Database''. Cambridge: MIT Press, 305-332.		Hirst, G., and St-Onge, D. (1998). [http://mirror.eacoss.org/documentation/ITLibrary/IRIS/Data/1997/Hirst/Lexical/1997-Hirst-Lexical.pdf Lexical chains as representation of context for the detection and correction of malapropisms]. In C. Fellbaum (ed.), ''WordNet: An Electronic Lexical Database''. Cambridge: MIT Press, 305-332.

Finin: /* Table of results */

2014-11-09T21:46:31Z

Table of results

← Older revision		Revision as of 21:46, 9 November 2014
Line 174:		Line 174:
	\| 92.50%		\| 92.50%
	\| 84.39-97.20%		\| 84.39-97.20%
			\|-
			\| LSA
			\| Han (2014)
			\| Han (2014)
			\| Hybrid
			\| 95.0%
			\| 87.69-98.62%
	\|-		\|-
	\| ADW		\| ADW

Taher: /* References */

2014-02-13T11:44:33Z

References

← Older revision		Revision as of 11:44, 13 February 2014
Line 246:		Line 246:
	Matveeva, I., Levow, G., Farahat, A., and Royer, C. (2005). [http://people.cs.uchicago.edu/~matveeva/SynGLSA_ranlp_final.pdf Generalized latent semantic analysis for term representation]. ''Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP-05)'', Borovets, Bulgaria.		Matveeva, I., Levow, G., Farahat, A., and Royer, C. (2005). [http://people.cs.uchicago.edu/~matveeva/SynGLSA_ranlp_final.pdf Generalized latent semantic analysis for term representation]. ''Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP-05)'', Borovets, Bulgaria.

	Pado, S., and Lapata, M. (2007). [www.nlpado.de/~sebastian/pub/papers/cl07_pado.pdf Dependency-based construction of semantic space models]. ''Computational Linguistics'', 33(2), 161-199.		Pado, S., and Lapata, M. (2007). [http://www.nlpado.de/~sebastian/pub/papers/cl07_pado.pdf Dependency-based construction of semantic space models]. ''Computational Linguistics'', 33(2), 161-199.

	Pilehvar, M.T., Jurgens D., and Navigli R. (2013). [http://wwwusers.di.uniroma1.it/~navigli/pubs/ACL_2013_Pilehvar_Jurgens_Navigli.pdf Align, disambiguate and walk: A unified approach for measuring semantic similarity]. ''Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013),'' Sofia, Bulgaria.		Pilehvar, M.T., Jurgens D., and Navigli R. (2013). [http://wwwusers.di.uniroma1.it/~navigli/pubs/ACL_2013_Pilehvar_Jurgens_Navigli.pdf Align, disambiguate and walk: A unified approach for measuring semantic similarity]. ''Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (ACL 2013),'' Sofia, Bulgaria.