ECNU: One Stone Two Birds: Ensemble of Heterogenous Measures for Semantic Relatedness and Textual Entailment

8th International Workshop on Semantic Evaluation, SemEval 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014, Proceedings

Volumn , Issue , 2014, Pages 271-277

  Zhao, Jiang ^a   Zhu, Tian Tian ^a   Lan, Man ^a  

^a EAST CHINA NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; SEMANTICS;

CLASSIFICATION TASKS; FEATURES SETS; SEMANTIC RELATEDNESS; SIMILARITY MEASURE; SUBTASK; TEXT SIMILARITY; TEXTUAL ENTAILMENT;

TEXT PROCESSING;

EID: 85107064777     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (24)

1. Ion Androutsopoulos and Prodromos Malakasiotis. 2009. A survey of paraphrasing and textual entailment methods. arXiv preprint arXiv:0912.3747.
2. Carmen Banea, Samer Hassan, Michael Mohler, and Rada Mihalcea. 2012. Unt:a supervised synergistic approach to semantictext similarity. In First Joint Conference on Lexical and Computational Semantics (*SEM.
3. Daniel Bär, Chris Biemann, Iryna Gurevych, and Torsten Zesch. 2012. Ukp: Computing semantic textual similarity by combining multiple content similarity measures. In Proceedings of the First Joint Conference on Lexical and Computational Semantics, pages 435–440. Association for Computational Linguistics.
4. Johan Bos and Katja Markert. 2005. Recognising textual entailment with logical inference. In Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing, pages 628–635. Association for Computational Linguistics.
5. Danilo Croce, Valerio Storch, and Roberto Basili. 2013. Unitor-core typed: Combining text similarity and semantic filters through sv regression. In Proceedings of the 2nd Joint Conference on Lexical and Computational Semantics, page 59.
6. Wael H Gomaa and Aly A Fahmy. 2013. A survey of text similarity approaches. International Journal of Computer Applications, 68(13):13–18.
7. Edward Grefenstette and Mehrnoosh Sadrzadeh. 2011. Experimental support for a categorical compositional distributional model of meaning. In Proceedings of the Conference on Empirical Methods in Natural Language Processing, pages 1394–1404. Association for Computational Linguistics.
8. Weiwei Guo and Mona Diab. 2012. Modeling sentences in the latent space. In Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics.
9. Zellig S Harris. 1954. Distributional structure. The Philosophy of Linguistics,.
10. Yuhua Li, David McLean, Zuhair A Bandar, James D O’shea, and Keeley Crockett. 2006. Sentence similarity based on semantic nets and corpus statistics. Knowledge and Data Engineering, IEEE Transactions on, 18(8):1138–1150.
11. Mihai C. Lintean and Vasile Rus. 2012. Measuring semantic similarity in short texts through greedy pairing and word semantics. In FLAIRS Conference. AAAI Press.
12. Prodromos Malakasiotis and Ion Androutsopoulos. 2007. Learning textual entailment using svms and string similarity measures. In Proceedings of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pages 42–47. Association for Computational Linguistics.
13. M. Marelli, L. Bentivogli, M. Baroni, R. Bernardi, S. Menini, and R. Zamparelli. 2014. Semeval-2014 task 1: Evaluation of compositional distributional semantic models on full sentences through semantic relatedness and textual entailment. In Proceedings of SemEval 2014: International Workshop on Semantic Evaluation.
14. Rada Mihalcea, Courtney Corley, and Carlo Strapparava. 2006. Corpus-based and knowledge-based measures of text semantic similarity. In AAAI, volume 6, pages 775–780.
15. Fabian Pedregosa, Gaël. Varoquaux, Alexandre Gram-fort, Vincent Michel, Bertrand Thirion, Olivier Grisel, Mathieu Blondel, Peter Prettenhofer, Ron Weiss, Vincent Dubourg, Jake Vanderplas, Alexandre Passos, David Cournapeau, Matthieu Brucher, Matthieu Perrot, and Édouard Duchesnay. 2011. Scikit-learn: Machine learning in Python. Journal of Machine Learning Research, 12:2825–2830.
16. Evan Sandhaus. 2008. The new york times annotated corpus ldc2008t19. Philadelphia: Linguistic Data Consortium.
17. Socher, Richard, Huval Brody, Manning Christopher, and Ng Andrew. 2012. Semantic compositionality through recursive matrix-vector spaces. In Proceedings of EMNLP, Jeju Island, Korea.
18. Peter D Turney, Patrick Pantel, et al. 2010. From frequency to meaning: Vector space models of semantics. Journal of artificial intelligence research, 37(1):141–188.
19. Frane Šarić, Goran Glavaš, Mladen Karan, Jan Šnajder, and Bojana Dalbelo Bašić. 2012. Takelab: Systems for measuring semantic text similarity. In Proceedings of the First Joint Conference on Lexical and Computational Semantics, pages 441–448, Stroudsburg, PA, USA. Association for Computational Linguistics.
20. Fabio Massimo Zanzotto, Ioannis Korkontzelos, Francesca Fallucchi, and Suresh Manandhar. 2010. Estimating linear models for compositional distributional semantics. In Proceedings of the 23rd International Conference on Computational Linguistics, pages 1263–1271. Association for Computational Linguistics.
21. Jiang Zhao, Man Lan, and Zheng-Yu Niu. 2013. Ecnucs: Recognizing cross-lingual textual entailment using multiple text similarity and text difference measures. In Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013), pages 118–123, Atlanta, Georgia, USA, June. Association for Computational Linguistics.
22. Jiang Zhao, Man Lan, Zheng-Yu Niu, and Donghong Ji. 2014. Recognizing cross-lingual textual entailment with co-training using similarity and difference views. In The 2014 International Joint Conference on Neural Networks (IJCNN2014). IEEE.
23. Zhi-Hua Zhou and Ming Li. 2005. Semi-supervised regression with co-training. In IJCAI, pages 908–916.
24. Tian Tian Zhu and Man Lan. 2013. Ecnucs: Measuring short text semantic equivalence using multiple similarity measurements. In Proceedings of the 2nd Joint Conference on Lexical and Computational Semantics, page 124.