An Importance-and-Semantics-Aware Approach for Entity Resolution Using MLP

Author:

Xu Yaoli,Li Zhanhuai,Qi Wanhua

Publisher

Springer Singapore

Reference21 articles.

1. Pennington, J., Socher, R., Manning, C.D.: Glove: global vectors for word representation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, pp. 1532–1543. ACL, Stroudsburg (2014)

2. Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. CoRR abs/1301.3781 (2013). http://arxiv.org/abs/1301.3781

3. Fan, F., Li, Z., Chen, Q., Liu, H.: An outlier-detection based approach for automatic entity matching. Chin. J. Comput. 40(10), 2197–2211 (2017). https://doi.org/10.11897/SP.J.1016.2017.02197

4. Köpcke, H., Thor, A., Rahm, E.: Evaluation of entity resolution approaches on real-world match problems. PVLDB 3(1), 484–493 (2010). https://doi.org/10.14778/1920841.1920904

5. Cohen, W.W., Ravikumar, P., Fienberg, S.E.: A comparison of string distance metrics for name-matching tasks. In: Proceedings of IJCAI-03 Workshop on Information Integration on the Web, pp. 73–78. AAAI Press, Palo Alto (2003)

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