Keping Bi

588 citations
14 papers · 153 · h-index 5

Impact in

    • Recommender Systems and Techniques
    • Web Data Mining and Analysis
    • Information Retrieval and Search Behavior
    • Topic Modeling
    • Advanced Graph Neural Networks
    • Text and Document Classification Technologies
    • Advanced Text Analysis Techniques

Papers in

    • Topic Modeling 5
    • Natural Language Processing Techniques 3
    • Text and Document Classification Technologies 3
    • Domain Adaptation and Few-Shot Learning 2
    • Information Retrieval and Search Behavior 4
    • Recommender Systems and Techniques 3
    • Web Data Mining and Analysis 3

Keping Bi

11 papers receiving 143 citations

Peers

Keping Bi
Comparison fields: 5 of 27
  • Information Systems 93
  • Artificial Intelligence 107
  • Computer Vision and Pattern Recognition 33
  • Computer Science Applications 6
  • Health Informatics 1
Replace Sarik Ghazarian with:
Sarik Ghazarian United States
Rolf Jagerman United States
Salvatore Romeo Qatar
Jinze Bai China
Sue Felshin United States
Yiheng Shu China
Thibault Formal France
Malgorzata Mochól Germany
Xin Rong United States
Prasad Pingali India
Keping Bi relative to Sarik Ghazarian United States Sarik Ghazarian's profile →
Citations per field
00.5×1.5×2.2×
Sarik Ghazarian · 1×
Citations per year

Countries citing papers authored by Keping Bi

Since Specialization
Citations

This map shows the geographic impact of Keping Bi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Keping Bi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keping Bi more than expected).

Fields of papers citing papers by Keping Bi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keping Bi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Keping Bi. The network helps show where Keping Bi may publish in the future.

Co-authors

The 19 scholars most cited alongside Keping Bi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Keping Bi Line = papers co-authored together Keping Bi links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 201787
2 201937
3 202112
4 20126
5 20234
6 20232
7 20241
8 20241
9 20241
10 20191
11 20231
12 20250
13 20240
14 20240

About Keping Bi

Keping Bi is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Management Science and Operations Research, having authored 14 papers that have together received 153 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Information Retrieval and Search Behavior (4 papers), Natural Language Processing Techniques (3 papers), Text and Document Classification Technologies (3 papers), Recommender Systems and Techniques (3 papers), Web Data Mining and Analysis (3 papers), Domain Adaptation and Few-Shot Learning (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Information Systems (93 citations), Artificial Intelligence (107 citations), Computer Vision and Pattern Recognition (33 citations), Computer Science Applications (6 citations) and Health Informatics (1 citation). Keping Bi has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Qingyao Ai, W. Bruce Croft, Xu Chen, Yongfeng Zhang, Yongfeng Zhang, Aslı Çelikyılmaz, Bruce Croft, Rahul Jha, Jiafeng Guo and Wei Chen. Their work appears in journals such as ACM Transactions on Information Systems, IEEE Transactions on Knowledge and Data Engineering and arXiv (Cornell University).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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