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Search & information retrieval

Improving how people discover, understand, and use information through advances in search and retrieval.

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Event

SIGIR 2022

July 11, 2022 – June 15, 2022 | Madrid, Spain

Microsoft is proud to be a sponsor of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (opens in new tab). Search and recommendation is core to many Microsoft offerings—such as…

Publication

Unsupervised Context Aware Sentence Representation Pretraining for Multi-lingual Dense Retrieval

Ning Wu, Yaobo Liang, Houxing Ren, Linjun Shou (寿林钧), Nan Duan, Ming Gong (YIMING), Daxin Jiang (姜大昕)

IJCAI 2022 | July 2022

Publication

Keynote: Searching for a New and Better Future of Work

Jaime Teevan

International ACM SIGIR Conference on Research and Development in Information Retrieval | July 2022

Publication

Ada-Ranker: A Data Distribution Adaptive Ranking Paradigm for Sequential Recommendation

Xinyan Fan, Jianxun Lian, Wayne Xin Zhao, Zheng Liu, Chaozhuo Li, Xing Xie

SIGIR 2022 | July 2022

Publication

A flexible framework for offline effectiveness metrics

Alistair Moffat, Joel Mackenzie, Paul Thomas, Leif Azzopardi

International ACM SIGIR Conference on Research and Development in Information Retrieval | July 2022

Publication

Are We There Yet? A Decision Framework for Replacing Term-Based Retrieval with Dense Retrieval Systems

Sebastian Hofstätter, Nick Craswell, Bhaskar Mitra, Hamed Zamani, Allan Hanbury

June 2022

Publication

Causal Inference in the Presence of Interference in Sponsored Search Advertising

Razieh Nabi, Joel Pfeiffer, Denis Charles, Emre Kiciman

Frontiers in Big Data | June 2022, Vol 5

Project

KDD 2022 Tutorial on Large-Scale Information Extraction under Privacy-Aware Constraints

In this digital age, people spend a significant portion of their lives online and this has led to an explosion of personal data from users and their activities. Typically, this data is private and no-body…

Publication

DebiasGAN: Eliminating Position Bias in News Recommendation with Adversarial Learning

Chuhan Wu, Fangzhao Wu, Yongfeng Huang

EMNLP 2022 | June 2022

Publication

Improving Relevance Modeling via Heterogeneous Behavior Graph Learning in Bing Ads

Chaozhuo Li, Bochen Pang, Yuming Liu, Jianxun Lian, Jianan Zhao, Hao Sun, Weiwei Deng, Xing Xie, Qi Zhang

KDD 2022 | June 2022

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