Session-Aware Query Auto-completion using Extreme Multi-Label Ranking

Author:

Yadav Nishant1,Sen Rajat2,Hill Daniel N.3,Mazumdar Arya4,Dhillon Inderjit S.5

Affiliation:

1. University of Massachusetts Amherst, Amherst, MA, USA

2. Google Research, San Francisco, CA, USA

3. Amazon, Berkeley, CA, USA

4. University of California, San Diego, San Diego, CA, USA

5. Amazon & University of Texas Austin, Berkeley, CA, USA

Publisher

ACM

Reference46 articles.

1. DiSMEC

2. Context-sensitive query auto-completion

3. Kush Bhatia Himanshu Jain Purushottam Kar Manik Varma and Prateek Jain. 2015. Sparse local embeddings for extreme multi-label classification. In Advances in Neural Information Processing Systems. 730--738. Kush Bhatia Himanshu Jain Purushottam Kar Manik Varma and Prateek Jain. 2015. Sparse local embeddings for extreme multi-label classification. In Advances in Neural Information Processing Systems. 730--738.

4. A Survey of Query Auto Completion in Information Retrieval

5. Time-sensitive Personalized Query Auto-Completion

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1. DAC: Quantized Optimal Transport Reward-based Reinforcement Learning Approach to Detoxify Query Auto-Completion;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10

2. On-Device Query Auto-completion for Email Search;Lecture Notes in Computer Science;2024

3. DQAC: Detoxifying Query Auto-completion with Adapters;Lecture Notes in Computer Science;2024

4. trie-nlg: trie context augmentation to improve personalized query auto-completion for short and unseen prefixes;Data Mining and Knowledge Discovery;2023-08-07

5. PECOS;Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2022-08-14

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