Yunbo Cao

79 papers receiving 1.9k citations

Hit Papers

Adapting ranking SVM to document retrieval20062026201220192006100200300

Peers

Yunbo Cao
Comparison fields: 5 of 83
  • Artificial Intelligence 1.6k
  • Information Systems 989
  • Computer Vision and Pattern Recognition 241
  • Computer Science Applications 224
  • Sociology and Political Science 157
Replace Noriko Kando with:
Noriko Kando Japan
Peter Bailey Australia
Marta Sabou Austria
Yücel Saygın Türkiye
Pasquale Lops Italy
Milad Shokouhi United Kingdom
Michael Bendersky United States
Guangyou Zhou China
Falk Scholer Australia
Yunbo Cao relative to Noriko Kando Japan Noriko Kando's profile →
Citations per field
00.5×4.0×
Noriko Kando · 1×
Citations per year

Countries citing papers authored by Yunbo Cao

Since Specialization
Citations

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

Fields of papers citing papers by Yunbo Cao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yunbo Cao

This figure shows the co-authorship network connecting the top 25 collaborators of Yunbo Cao. A scholar is included among the top collaborators of Yunbo Cao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yunbo Cao. Yunbo Cao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 28
2 21
3 4
4 2
5 22
6 6
7 13
8 23
9 4
10 13
11 27
12
A Statistical Framework for Product Description Generation
17
13
A Lazy Learning Model for Entity Linking using Query-Specific Information
1
14
I2R-NUS-MSRA at TAC 2011: Entity Linking.
9
15
MSRA at TAC 2011: Entity Linking
2
16
Searching Questions by Identifying Question Topic and Question Focus
98
17
A Probabilistic Model for Fine-Grained Expert Search
2
18
Low-Quality Product Review Detection in Opinion Summarization
250
19
Research on Enterprise Track of TREC 2007 at SJTU APEX Lab
10
20
Research on Expert Search at Enterprise Track of TREC 2005.
68

About Yunbo Cao

Yunbo Cao is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems, having authored 79 papers that have together received 2.0k indexed citations. Recurring topics across this work include Topic Modeling (47 papers), Natural Language Processing Techniques (35 papers) and Expert finding and Q&A systems (13 papers). The work is most often cited by research in Artificial Intelligence (1.6k citations), Information Systems (989 citations) and Computer Science Applications (224 citations). Yunbo Cao has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Chin-Yew Lin, Yalou Huang, Hang Li, Yong Yu, Hsiao-Wuen Hon, Jun Xu, Tie‐Yan Liu, Ming Zhou, Jingjing Liu and Shenghua Bao. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Information Processing & Management and ACM Transactions on Information 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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