Improving the Efficiency and Effectiveness for BERT-based Entity Resolution

Author:

Li Bing,Miao Yukai,Wang Yaoshu,Sun Yifang,Wang Wei

Abstract

BERT has set a new state-of-the-art performance on entity resolution (ER) task, largely owed to fine-tuning pre-trained language models and the deep pair-wise interaction. Albeit being remarkably effective, it comes with a steep increase in computational cost, as the deep-interaction requires to exhaustively compute every tuple pair to search for co-references. For ER task, it is often prohibitively expensive due to the large cardinality to be matched. To tackle this, we introduce a siamese network structure that independently encodes tuples using BERT but delays the pair-wise interaction via an enhanced alignment network. This siamese structure enables a dedicated blocking module to quickly filter out obviously dissimilar tuple pairs, and thus drastically reduces the cardinality of fine-grained matching. Further, the blocking and entity matching are integrated into a multi-task learning framework for facilitating both tasks. Extensive experiments on multiple datasets demonstrate that our model significantly outperforms state-of-the-art models (including BERT) in both efficiency and effectiveness.

Publisher

Association for the Advancement of Artificial Intelligence (AAAI)

Subject

General Medicine

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Leveraging Knowledge Graphs for Matching Heterogeneous Entities and Explanation;2023 IEEE International Conference on Big Data (BigData);2023-12-15

2. SBTREC - A Transformer Framework for Personalized Tour Recommendation Problem with Sentiment Analysis;2023 IEEE International Conference on Big Data (BigData);2023-12-15

3. CampER: An Effective Framework for Privacy-Aware Deep Entity Resolution;Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2023-08-04

4. Effective entity matching with transformers;The VLDB Journal;2023-01-17

5. Adaptive deep learning for entity resolution by risk analysis;Knowledge-Based Systems;2023-01

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