3 citations · 4 across the 6 of their papers we have counts for
6 papers
JourneyFormer: Encoding Airbnb Guest Journey with Sequence Modeling
Daochen Zha, Chun How Tan, Xin Liu +9
Sequence modeling has become increasingly popular in recommendation and ranking algorithms, owing to its capacity to model users' historical behaviors and infer user intentions. De…
CASTLE: Contrastive and Seed-Guided Training for Cold-Start Natural Language Search
Wendy Ran Wei, Hao Li, Weiwei Guo +9
Deploying natural language search systems presents a critical cold-start challenge: no real user queries to learn linguistic patterns, and no relevance labels to train ranking mode…
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…
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…
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…
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…