Difference between revisions of "Paraphrase Identification (State of the art)"
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! Accuracy | ! Accuracy | ||
! F | ! F | ||
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| + | | RMLMG | ||
| + | | Rus et al. (2008) | ||
| + | | unsupervised graph subsumption | ||
| + | | 70.6% | ||
| + | | 80.5% | ||
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| MCS | | MCS | ||
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Mihalcea, R., Corley, C., and Strapparava, C. (2006). [http://reference.kfupm.edu.sa/content/c/o/corpus_based_and_knowledge_based_measure_3759629.pdf Corpus-based and knowledge-based measures of text semantic similarity], ''Proceedings of the National Conference on Artificial Intelligence (AAAI 2006)'', Boston, Massachusetts, pp. 775-780. | Mihalcea, R., Corley, C., and Strapparava, C. (2006). [http://reference.kfupm.edu.sa/content/c/o/corpus_based_and_knowledge_based_measure_3759629.pdf Corpus-based and knowledge-based measures of text semantic similarity], ''Proceedings of the National Conference on Artificial Intelligence (AAAI 2006)'', Boston, Massachusetts, pp. 775-780. | ||
| + | |||
| + | Rus, V. and McCarthy, P.M. and Lintean, M.C. and McNamara, D.S. and Graesser, A.C. (2008). [http://csep.psyc.memphis.edu/McNamara/pdf/Paraphrase_Identification.pdf Paraphrase identification with lexico-syntactic graph subsumption], ''FLAIRS 2008'', pp. 201-206. | ||
Wan, S., Dras, M., Dale, R., and Paris, C. (2006). [http://www.alta.asn.au/events/altw2006/proceedings/swan-final.pdf Using dependency-based features to take the "para-farce" out of paraphrase], ''Proceedings of the Australasian Language Technology Workshop (ALTW 2006)'', pp. 131-138. | Wan, S., Dras, M., Dale, R., and Paris, C. (2006). [http://www.alta.asn.au/events/altw2006/proceedings/swan-final.pdf Using dependency-based features to take the "para-farce" out of paraphrase], ''Proceedings of the Australasian Language Technology Workshop (ALTW 2006)'', pp. 131-138. | ||
Revision as of 13:23, 24 March 2009
- source: Microsoft Research Paraphrase Corpus (MSRP)
- task: given a pair of sentences, classify them as paraphrases or not paraphrases
- see: Dolan et al. (2004)
- train: 4,076 sentence pairs (2,753 positive: 67.5%)
- test: 1,725 sentence pairs (1,147 positive: 66.5%)
Sample data
- Sentence 1: Amrozi accused his brother, whom he called "the witness", of deliberately distorting his evidence.
- Sentence 2: Referring to him as only "the witness", Amrozi accused his brother of deliberately distorting his evidence.
- Class: 1 (true paraphrase)
Table of results
| Algorithm | Reference | Description | Accuracy | F |
|---|---|---|---|---|
| RMLMG | Rus et al. (2008) | unsupervised graph subsumption | 70.6% | 80.5% |
| MCS | Mihalcea et al. (2006) | unsupervised combination of several word similarity measures | 70.3% | 81.3% |
| WDDP | Wan et al. (2006) | supervised dependency-based features | 75.6% | 83.0% |
References
Dolan, B., Quirk, C., and Brockett, C. (2004). Unsupervised construction of large paraphrase corpora: Exploiting massively parallel news sources, Proceedings of the 20th international conference on Computational Linguistics (COLING 2004), Geneva, Switzerland, pp. 350-356.
Mihalcea, R., Corley, C., and Strapparava, C. (2006). Corpus-based and knowledge-based measures of text semantic similarity, Proceedings of the National Conference on Artificial Intelligence (AAAI 2006), Boston, Massachusetts, pp. 775-780.
Rus, V. and McCarthy, P.M. and Lintean, M.C. and McNamara, D.S. and Graesser, A.C. (2008). Paraphrase identification with lexico-syntactic graph subsumption, FLAIRS 2008, pp. 201-206.
Wan, S., Dras, M., Dale, R., and Paris, C. (2006). Using dependency-based features to take the "para-farce" out of paraphrase, Proceedings of the Australasian Language Technology Workshop (ALTW 2006), pp. 131-138.