Semantic representations for domain adaptation: A case study on the tree kernel-based method for relation extraction

ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference

Volumn 1, Issue , 2015, Pages 635-644

  Nguyen, Thien Huu ^a   Plank, Barbara ^b   Grishman, Ralph ^a  

^a POLYTECHNIC UNIVERSITY   (United States)

^b UNIVERSITY OF COPENHAGEN   (Denmark)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; EXTRACTION; FORESTRY; SEMANTICS;

DOMAIN ADAPTATION; FEATURE BASED APPROACHES; FEATURE-BASED METHOD; GAIN INSIGHT; GENERALIZATION PERFORMANCE; KERNEL BASED METHODS; RELATION EXTRACTION; SEMANTIC REPRESENTATION;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84943777848     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3115/v1/p15-1062     Document Type: Conference Paper

References (45)

1. Marco Baroni and Roberto Zamparelli. 2010. Nouns are vectors, adjectives are matrices: Representing adjective-noun constructions in semantic space. In EMNLP.
2. Marco Baroni, Silvia Bernardini, Adriano Ferraresi, and Eros Zanchetta. 2009. The WaCky wide web: A collection of very large linguistically processed web-crawled corpora. In Language Resources and Evaluation, pages 209-226.
3. Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. 2003. A neural probabilistic language model. In Journal of Machine Learning Research 3, pages 1137-1155.
4. William Blacoe and Mirella Lapata. 2012. A comparison of vector-based representations for semantic composition. In EMNLP.
5. John Blitzer, Ryan McDonald, and Fernando Pereira. 2006. Domain adaptation with structural correspondence learning. In EMNLP.
6. John Blitzer, Mark Dredze, and Fernando Pereira. 2007. Biographies, bollywood, boom-boxes and blenders: Domain adaptation for sentiment classification. In ACL.
7. Stephan Bloehdorn and Alessandro Moschitti. 2007. Exploiting Structure and Semantics for Expressive Text Kernels. In CIKM.
8. Peter F. Brown, Peter V. deSouza, Robert L. Mercer, Vincent J. Della Pietra, and Jenifer C. Lai. 1992. Class-based n-gram models of natural language. In Computational Linguistics, pages 467-479.
9. Razvan C. Bunescu and Raymond J. Mooney. 2005. A shortest path dependency kernel for relation extraction. In EMNLP.
10. Razvan C. Bunescu. 2007. Learning to extract relations from the web using minimal supervision. In ACL.
11. Yee Seng Chan and Dan Roth. 2010. Exploiting background knowledge for relation extraction. In COLING.
12. Hal Daume. 2007. Frustratingly easy domain adaptation. In ACL.
13. Ralph Grishman, DavidWestbrook, and Adam Meyers. 2005. Nyus english ace 2005 system description. In The ACE 2005 Evaluation Workshop.
14. Fei Huang and Alexander Yates. 2010. Exploring representation-learning approaches to domain adaptation. In The ACLWorkshop on Domain Adaptation for Natural Language Processing (DANLP).
15. Jing Jiang and ChengXiang Zhai. 2007a. A systematic exploration of the feature space for relation extraction. In NAACL-HLT.
16. Jing Jiang and ChengXiang Zhai. 2007b. Instance weighting for domain adaptation in nlp. In ACL.
17. Nanda Kambhatla. 2004. Combining lexical, syntactic, and semantic features with maximum entropy models for information extraction. In ACL.
18. Pavel Kuksa, Yanjun Qi, Bing Bai, Ronan Collobert, Jason Weston, Vladimir Pavlovic, and Xia Ning. 2010. Semi-supervised abstractionaugmented string kernel for multi-level bio-relation extraction. In ECML PKDD.
19. Andriy Mnih and Geoffrey Hinton. 2008. A scalable hierarchical distributed language model. In NIPS.
20. Alessandro Moschitti. 2006. Efficient convolution kernels for dependency and constituent syntactic trees. In ECML.
21. Alessandro Moschitti. 2008. Kernel methods, syntax and semantics for relational text categorization. In CIKM.
22. Thien Huu Nguyen and Ralph Grishman. 2014. Employing word representations and regularization for domain adaptation of relation extraction. In ACL.
23. Thien Huu Nguyen and Ralph Grishman. 2015. Relation extraction: Perspective from convolutional neural networks. In The NAACL Workshop on Vector Space Modeling for NLP (VSM).
24. T. Truc-Vien Nguyen, Alessandro Moschitti, and Giuseppe Riccardi. 2009. Convolution kernels on constituent, dependency and sequential structures for relation extraction. In EMNLP.
25. Luan Minh Nguyen, W. Ivor Tsang, A. Kian Ming Chai, and Leong Hai Chieu. 2014. Robust domain adaptation for relation extraction via clustering consistency. In ACL.
26. Denis Paperno, The Nghia Pham, and Marco Baroni. 2014. A practical and linguistically-motivated approach to compositional distributional semantics. In ACL.
27. Ted Pedersen. 2008. Empiricism is not a matter of faith. In Computational Linguistics 3, pages 465-470.
28. Slav Petrov and Ryan McDonald. 2012. Overview of the 2012 shared task on parsing the web. In The First Workshop on Syntactic Analysis of Non-Canonical Language (SANCL).
29. Barbara Plank and Alessandro Moschitti. 2013. Embedding semantic similarity in tree kernels for domain adaptation of relation extraction. In ACL.
30. Longhua Qian, Guodong Zhou, Fang Kong, Qiaoming Zhu, and Peide Qian. 2008. Exploiting constituent dependencies for tree kernel-based semantic relation extraction. In COLING.
31. Richard Socher, Alex Perelygin, Jean Y. Wu, Jason Chuang, Christopher D. Manning, Andrew Y. Ng, and Christopher Potts. 2012a. Recursive deep models for semantic compositionality over a sentiment treebank. In EMNLP-CoNLL.
32. Richard Socher, Brody Huval, Christopher D. Manning, and Andrew Y. Ng. 2012b. Semantic compositionality through recursive matrix-vector spaces. In EMNLP.
33. Lucas Sterckx, Thomas Demeester, Johannes Deleu, and Chris Develder. 2014. Using active learning and semantic clustering for noise reduction in distant supervision. In AKBC.
34. Ang Sun, Ralph Grishman, and Satoshi Sekine. 2011. Semi-supervised relation extraction with large-scale word clustering. In ACL.
35. Joseph Turian, Lev-Arie Ratinov, and Yoshua Bengio. 2010. Word representations: A simple and general method for semi-supervised learning. In ACL.
36. Mengqiu Wang. 2008. A re-examination of dependency path kernels for relation extraction. In IJCNLP.
37. Markus Werning, Edouard Machery, and Gerhard Schurz. 2006. Compositionality of meaning and content: Foundational issues (linguistics & philosophy). In Linguistics & philosophy.
38. Min Xiao and Yuhong Guo. 2013. Domain adaptation for sequence labeling tasks with a probabilistic language adaptation model. In ICML.
39. Mo Yu, Matthew Gormley, and Mark Dredze. 2014. Factor-based compositional embedding models. In The NIPS workshop on Learning Semantics.
40. Mo Yu, Matthew Gormley, and Mark Dredze. 2015. Combining word embeddings and feature embeddings for fine-grained relation extraction. In NAACL.
41. Dmitry Zelenko, Chinatsu Aone, and Anthony Richardella. 2003. Kernel methods for relation extraction. In Journal of Machine Learning Research 3, pages 1083-1106.
42. Daojian Zeng, Kang Liu, Siwei Lai, Guangyou Zhou, and Jun Zhao. 2014. Relation classification via convolutional deep neural network. In COLING.
43. Min Zhang, Jie Zhang, Jian Su, and Guodong Zhou. 2006. A composite kernel to extract relations between entities with both flat and structured features. In COLING-ACL.
44. Shubin Zhao and Ralph Grishman. 2005. Extracting relations with integrated information using kernel methods. In ACL.
45. GuoDong Zhou, Jian Su, Jie Zhang, and Min Zhang. 2005. Exploring various knowledge in relation extraction. In ACL.