A brief introduction about myself: ai.google/research/peopl…

The paper will be presented during ACM SIGIR 2019 by Michael Bendersky. Innovative technology with practical applications. Please come and enjoy the talk with us.

I'll be presenting our paper "Dynamic Language Models for Continuously Evolving Content" at #KDD2021 in the ADS Track (Session-10: Web Mining) on August 16th 10.30 AM PT/August 17th 1.30 AM SGT. This is a joint work with Tao Chen, Mingyang (Michael) Zhang, Michael Bendersky, and Marc Najork.

Our paper "Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models" (by Tao Chen Mingyang Zhang Jing Lu Michael Bendersky Marc Najork; To appear in ECIR, 2022) is now on arXiv: arxiv.org/abs/2201.10582

3.1 "Job Type Extraction for Service Businesses" research.google/pubs/pub52102/ by Cheng Li, Y. Qi, H. Zakarian, Michael Bendersky, Y. Wu and Marc Najork describes a large-scale pipeline for high-precision automatic extraction of job types from websites of business owners.

🎉Congratulations!🎉 BEST SHORT PAPER AWARD #SIGIR2023 #Taipei

Very honored to receive the best short paper award at #SIGIR2023! Will present the work at 12 in room 201E today. "SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval" w/ Jeffrey M. Dudek, Cheng Li, Mingyang Zhang Michael Bendersky