Improving Session Search by Modeling Multi-Granularity Historical Query Change-Reference-Cited by-同舟云学术

Improving Session Search by Modeling Multi-Granularity Historical Query Change

Published:2022-02-11 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining
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Author:

Zuo Xiaochen¹,Dou Zhicheng²,Wen Ji-Rong²

Affiliation:

1. Renmin University of China, Beijing, China

2. Remin University of China, Beijing, China

Funder

National Natural Science Foundation of China

China Unicom Innovation Ecological Cooperation Plan

Intelligent Social Governance Platform, Major Innovation & Planning Interdisciplinary

Platform for the Double-First Class Initiative, Renmin University of China

Beijing Outstanding Young Scientist Program

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3488560.3498415

Reference34 articles.

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2. Wasi Uddin Ahmad , Kai-Wei Chang , and Hongning Wang . 2018. Multi-Task Learning for Document Ranking and Query Suggestion . In 6th International Conference on Learning Representations, ICLR 2018 , Vancouver, BC , Canada, April 30 - May 3, 2018, Conference Track Proceedings. OpenReview .net. https://openreview.net/forum?id=SJ1nzBeA- Wasi Uddin Ahmad, Kai-Wei Chang, and Hongning Wang. 2018. Multi-Task Learning for Document Ranking and Query Suggestion. In 6th International Conference on Learning Representations, ICLR 2018, Vancouver, BC, Canada, April 30 - May 3, 2018, Conference Track Proceedings. OpenReview.net. https://openreview.net/forum?id=SJ1nzBeA-

3. Wasi Uddin Ahmad Kai-Wei Chang and Hongning Wang. 2019. Context Attentive Document Ranking and Query Suggestion. In SIGIR. ACM 385--394. Wasi Uddin Ahmad Kai-Wei Chang and Hongning Wang. 2019. Context Attentive Document Ranking and Query Suggestion. In SIGIR. ACM 385--394.

4. Towards context-aware search by learning a very large variable length hidden markov model from search logs

5. TianGong-ST

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