Embedding semantic similarity in tree kernels for domain adaptation of relation extraction

Barbara Plank, Alessandro Moschitti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

57 Citations (Scopus)

Abstract

Relation Extraction (RE) is the task of extracting semantic relationships between entities in text. Recent studies on relation extraction are mostly supervised. The clear drawback of supervised methods is the need of training data: labeled data is expensive to obtain, and there is often a mismatch between the training data and the data the system will be applied to. This is the problem of domain adaptation. In this paper, we propose to combine (i) term generalization approaches such as word clustering and latent semantic analysis (LSA) and (ii) structured kernels to improve the adaptability of relation extractors to new text genres/domains. The empirical evaluation on ACE 2005 domains shows that a suitable combination of syntax and lexical generalization is very promising for domain adaptation.

Original languageEnglish
Title of host publicationACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages1498-1507
Number of pages10
Volume1
ISBN (Print)9781937284503
Publication statusPublished - 1 Jan 2013
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: 4 Aug 20139 Aug 2013

Other

Other51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
CountryBulgaria
CitySofia
Period4/8/139/8/13

Fingerprint

semantics
mismatch
syntax
genre
Semantic Similarity
Kernel
evaluation

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

Cite this

Plank, B., & Moschitti, A. (2013). Embedding semantic similarity in tree kernels for domain adaptation of relation extraction. In ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Vol. 1, pp. 1498-1507). Association for Computational Linguistics (ACL).

Embedding semantic similarity in tree kernels for domain adaptation of relation extraction. / Plank, Barbara; Moschitti, Alessandro.

ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Vol. 1 Association for Computational Linguistics (ACL), 2013. p. 1498-1507.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Plank, B & Moschitti, A 2013, Embedding semantic similarity in tree kernels for domain adaptation of relation extraction. in ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. vol. 1, Association for Computational Linguistics (ACL), pp. 1498-1507, 51st Annual Meeting of the Association for Computational Linguistics, ACL 2013, Sofia, Bulgaria, 4/8/13.
Plank B, Moschitti A. Embedding semantic similarity in tree kernels for domain adaptation of relation extraction. In ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Vol. 1. Association for Computational Linguistics (ACL). 2013. p. 1498-1507
Plank, Barbara ; Moschitti, Alessandro. / Embedding semantic similarity in tree kernels for domain adaptation of relation extraction. ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference. Vol. 1 Association for Computational Linguistics (ACL), 2013. pp. 1498-1507
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