Understanding the role of human-inspired heuristics for retrieval models

Author:

Li Xiangsheng,Liu Yiqun,Mao Jiaxin

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science,Theoretical Computer Science

Reference32 articles.

1. Li X S, Mao J X, Wang C, Liu Y Q, Zhang M, Ma S P. Understanding reading attention distribution during relevance judgement. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval. 2019, 795–804

2. Pang L, Lan Y Y, Guo J F, Xu J, Cheng X Q. Deeprank: a new deep architecture for relevance ranking in information retrieval. In: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. 2017

3. Hu B T, Lu Z D, Li H, Chen Q C. Convolutional neural network architectures for matching natural language sentences. In: Proceedings of the 27th International Conference on Neural Information Processing Systems. 2014, 2042–2050

4. Huang P S, He X D, Gao J F, Deng L, Acero A, Heck L. Learning deep structured semantic models for Web search using clickthrough data. In: Proceedings of the 22nd ACM International Conference on Information and Knowledge Management. 2013, 2333–2338

5. Li X S, Liu Y Q, Mao J X, He Z X, Zhang M, Ma S P. Understanding reading attention distribution during relevance judgement. In: Proceedings of the 27th ACM International Conference on Information and Knowledge Management. 2018, 733–742

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