Improving taxonomic relation learning via incorporating relation descriptions into word embeddings-Reference-Cited by-同舟云学术

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Improving taxonomic relation learning via incorporating relation descriptions into word embeddings

Published:2020-03-04 Issue:14 Volume:32 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Huang Subin¹²^ORCID,Luo Xiangfeng¹,Huang Jing³,Wang Hao¹,Gu Shengwei¹⁴,Guo Yike¹⁵

Affiliation:

1. School of Computer Engineering and ScienceShanghai University Shanghai China

2. School of Computer and InformationAnhui Polytechnic University Wuhu China

3. Ant Financial Services Group Hangzhou China

4. School of Computer and Information EngineeringChuzhou University Chuzhou China

5. Data Science InstituteImperial College London London UK

Funder

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5696

Reference45 articles.

1. TaxoFinder: A Graph-Based Approach for Taxonomy Learning

2. Extracting location and creator-related information from Wikipedia-based information-rich taxonomy for ConceptNet expansion

3. WangJ WangZ ZhangD YanJ. Combining knowledge with deep convolutional neural networks for short text classification. Paper presented at: Proceedings of the 26th International Joint Conference on Artificial Intelligence IJCAI;2017:2915‐2921.

4. A distributed parallel algorithm for inferring hierarchical groups from large-scale text corpuses

5. An unsupervised approach for learning a Chinese IS-A taxonomy from an unstructured corpus

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