38 citations · 58 across the 5 of their papers we have counts for
7 papers
Deep Job Understanding at LinkedIn
Shan Li, Baoxu Shi, Jaewon Yang +4
As the world's largest professional network, LinkedIn wants to create economic opportunity for everyone in the global workforce. One of its most critical missions is matching jobs…
Salience and Market-aware Skill Extraction for Job Targeting
Baoxu Shi, Jaewon Yang, Feng Guo +1
At LinkedIn, we want to create economic opportunity for everyone in the global workforce. To make this happen, LinkedIn offers a reactive Job Search system, and a proactive Jobs Yo…
Learning to Ask Screening Questions for Job Postings
Baoxu Shi, Shan Li, Jaewon Yang +2
At LinkedIn, we want to create economic opportunity for everyone in the global workforce. A critical aspect of this goal is matching jobs with qualified applicants. To improve hiri…
Representation Learning in Heterogeneous Professional Social Networks with Ambiguous Social Connections
Baoxu Shi, Jaewon Yang, Tim Weninger +2
Network representations have been shown to improve performance within a variety of tasks, including classification, clustering, and link prediction. However, most models either foc…
Visualizing the Flow of Discourse with a Concept Ontology
Baoxu Shi, Tim Weninger
Understanding and visualizing human discourse has long being a challenging task. Although recent work on argument mining have shown success in classifying the role of various sente…
Neural Tensor Factorization
Xian Wu, Baoxu Shi, Yuxiao Dong +2
Neural collaborative filtering (NCF) and recurrent recommender systems (RRN) have been successful in modeling user-item relational data. However, they are also limited in their ass…