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Shuqing Bian

Renmin University of China

4 papers hereh-index 12938 citations14 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL3
  • cs.IR1
affiliations
  • Renmin University of China
same name
  • Shuqing Bian — 1 paper

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20182022
most citedImproving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion

17 citations · 22 across the 3 of their papers we have counts for

collaborators

4 papers

cs.IR2022

Leveraging Search History for Improving Person-Job Fit

Yupeng Hou, Xingyu Pan, Wayne Xin Zhao +4

As the core technique of online recruitment platforms, person-job fit can improve hiring efficiency by accurately matching job positions with qualified candidates. However, existin…

cs.CL2020★ 5 cited

Learning to Match Jobs with Resumes from Sparse Interaction Data using Multi-View Co-Teaching Network

Shuqing Bian, Xu Chen, Wayne Xin Zhao +5

With the ever-increasing growth of online recruitment data, job-resume matching has become an important task to automatically match jobs with suitable resumes. This task is typical…

cs.CL2020★ 17 cited

Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion

Kun Zhou, Wayne Xin Zhao, Shuqing Bian +3

Conversational recommender systems (CRS) aim to recommend high-quality items to users through interactive conversations. Although several efforts have been made for CRS, two major…

cs.CL2018

IcoRating: A Deep-Learning System for Scam ICO Identification

Shuqing Bian, Zhenpeng Deng, Fei Li +9

Cryptocurrencies (or digital tokens, digital currencies, e.g., BTC, ETH, XRP, NEO) have been rapidly gaining ground in use, value, and understanding among the public, bringing asto…

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