most citedEfficient Neural Query Auto Completion

24 citations · 31 across the 6 of their papers we have counts for

collaborators

7 papers

cs.IR2021

Deep Natural Language Processing for LinkedIn Search

Weiwei Guo, Xiaowei Liu, Sida Wang +7

Many search systems work with large amounts of natural language data, e.g., search queries, user profiles, and documents. Building a successful search system requires a thorough un…

cs.IR20213 cited

Incremental Learning for Personalized Recommender Systems

Yunbo Ouyang, Jun Shi, Haichao Wei +1

Ubiquitous personalized recommender systems are built to achieve two seemingly conflicting goals, to serve high quality content tailored to individual user's taste and to adapt qui…

cs.CL2021

Deep Natural Language Processing for LinkedIn Search Systems

Weiwei Guo, Xiaowei Liu, Sida Wang +6

Many search systems work with large amounts of natural language data, e.g., search queries, user profiles and documents, where deep learning based natural language processing techn…

cs.CL20203 cited

Deep Search Query Intent Understanding

Xiaowei Liu, Weiwei Guo, Huiji Gao +1

Understanding a user's query intent behind a search is critical for modern search engine success. Accurate query intent prediction allows the search engine to better serve the user…

cs.CL202024 cited

Efficient Neural Query Auto Completion

Sida Wang, Weiwei Guo, Huiji Gao +1

Query Auto Completion (QAC), as the starting point of information retrieval tasks, is critical to user experience. Generally it has two steps: generating completed query candidates…

cs.IR20201 cited

DeText: A Deep Text Ranking Framework with BERT

Weiwei Guo, Xiaowei Liu, Sida Wang +8

Ranking is the most important component in a search system. Mostsearch systems deal with large amounts of natural language data,hence an effective ranking system requires a deep un…