However, there has been no attempt to exploit GNN to create taxonomies. Recently Graph Neural Network (GNN) has shown to be powerful in successfully tackling many tasks. Publisher = "Association for Computational Linguistics",Ībstract = "Extracting lexico-semantic relations as graph-structured taxonomies, also known as taxonomy construction, has been beneficial in a variety of NLP applications.
DOMAIN GRAPH MODS
Cite (Informal): Taxonomy Construction of Unseen Domains via Graph-based Cross-Domain Knowledge Transfer (Shang et al., ACL 2020) Copy Citation: BibTeX Markdown MODS XML Endnote More options… PDF: Video: = "Taxonomy Construction of Unseen Domains via Graph-based Cross-Domain Knowledge Transfer",īooktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics", Association for Computational Linguistics.
In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pages 2198–2208, Online. Taxonomy Construction of Unseen Domains via Graph-based Cross-Domain Knowledge Transfer. Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya, and Alfio Gliozzo. Anthology ID: 2020.acl-main.199 Volume: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics Month: July Year: 2020 Address: Online Venue: ACL SIG: Publisher: Association for Computational Linguistics Note: Pages: 2198–2208 Language: URL: DOI: 10.18653/v1/2020.acl-main.199 Bibkey: shang-etal-2020-taxonomy Cite (ACL): Chao Shang, Sarthak Dash, Md. Experiments on benchmark datasets from science and environment domains show that our approach attains significant improvements correspondingly over the state of the art. The learned model is then used to generate taxonomy for a new unknown domain given a set of terms for that domain. Specifically, our proposed Graph2Taxo uses a noisy graph constructed from automatically extracted noisy hyponym hypernym candidate pairs, and a set of taxonomies for some known domains for training. We also propose a novel method of directed acyclic graph (DAG) generation for taxonomy construction. Our main contribution is to learn the latent features of taxonomy construction from existing domains to guide the structure learning of an unseen domain. In this paper, we propose Graph2Taxo, a GNN-based cross-domain transfer framework for the taxonomy construction task. Abstract Extracting lexico-semantic relations as graph-structured taxonomies, also known as taxonomy construction, has been beneficial in a variety of NLP applications.
The domain of a function signifies the inputs to the function and the range are the possible outputs for the given inputs. What is Domain and Range?įor functions, we input varying numbers and we receive new numbers as the outcome of the operation performed.
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With this article, we will learn what is the domain and range of a function, How to find them for exponential functions, trigonometric functions, absolute value function, square root function and so on with solved examples and more. Mapping or transformation is applied to express a function in mathematics. A function in relations and functions is imagined as a rule, which provides a unique output for all input.
We can also say that after substituting the domain, the complete set of all values achievable as outcomes of the dependent variable is said to be the range.
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