Bo Long

806 citations
21 papers · 506 · h-index 10

Impact in

Papers in

    • Recommender Systems and Techniques 13
    • Web Data Mining and Analysis 4
    • Expert finding and Q&A systems 3
    • Topic Modeling 5
    • Sentiment Analysis and Opinion Mining 2
    • Advanced Graph Neural Networks 2

Bo Long

20 papers receiving 490 citations

Peers

Bo Long
Comparison fields: 5 of 59
  • Information Systems 381
  • Artificial Intelligence 304
  • Management Science and Operations Research 107
  • Computer Vision and Pattern Recognition 106
  • Internal Medicine 13
Replace Balázs Hidasi with:
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Hande Dong China
Mohammad Yahya H. Al-Shamri Saudi Arabia
P. Dolan United States
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Citations per field
00.5×4.2×
Balázs Hidasi · 1×
Citations per year

Countries citing papers authored by Bo Long

Since Specialization
Citations

This map shows the geographic impact of Bo Long'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 Bo Long with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bo Long more than expected).

Fields of papers citing papers by Bo Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bo Long. 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 Bo Long. The network helps show where Bo Long may publish in the future.

Co-authors

The 25 scholars most cited alongside Bo Long, 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 Bo Long Line = papers co-authored together Bo Long links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011108
2 202277
3 201154
4 201652
5 201447
6 202136
7 202235
8 202323
9 202216
10 202210
11 20229
12 20148
13 20206
14 20234
15 20234
16 20234
17 20244
18
Learning to Generate Visual Questions with Noisy Supervision
20214
19 20234
20 20201

About Bo Long

Bo Long is a scholar working on Information Systems, Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research and Computer Networks and Communications, having authored 21 papers that have together received 506 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (13 papers), Advanced Bandit Algorithms Research (5 papers), Topic Modeling (5 papers), Web Data Mining and Analysis (4 papers), Image Retrieval and Classification Techniques (3 papers), Expert finding and Q&A systems (3 papers), Sentiment Analysis and Opinion Mining (2 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Information Systems (381 citations), Artificial Intelligence (304 citations), Management Science and Operations Research (107 citations), Computer Vision and Pattern Recognition (106 citations) and Internal Medicine (13 citations). Bo Long has collaborated with scholars based in United States, China and Canada. Frequent co-authors include Deepak Agarwal, Bee-Chung Chen, Alexander J. Smola, Zhaohui Zheng, Hongyuan Zha, Shuang-Hong Yang, Lingfei Wu, Zhihua Wei, Fangli Xu and Qi Shen. Their work appears in journals such as AI Magazine, ACM Transactions on Intelligent Systems and Technology, Frontiers in Cardiovascular Medicine, arXiv (Cornell University) and Neural Information Processing Systems.

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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