Junfeng Qu

19 papers receiving 519 citations

Junfeng Qu's Hit Papers

Mining high utility itemsets without candidate generation 2012 · 430 citations
4300+4+9Years since publication100200300400

Peers

Junfeng Qu
Comparison fields: 5 of 47
  • Computational Theory and Mathematics 349
  • Information Systems 477
  • Signal Processing 163
  • Artificial Intelligence 268
  • Marketing 35
Replace Heungmo Ryang with:
Heungmo Ryang South Korea
Guo-Cheng Lan Taiwan
Zhigang Zheng Australia
Ted Gueniche Canada
Manuel Calimlim United States
Antonio Gomariz Spain
Masashi Kiyomi Japan
Ada W. C. Fu Hong Kong
Yu-Chiang Li Taiwan
Sergei Obiedkov Russia
Junfeng Qu relative to Heungmo Ryang South Korea Heungmo Ryang's profile →
Citations per field
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Heungmo Ryang · 1×
Citations per year

Countries citing papers authored by Junfeng Qu

Since Specialization
Citations

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

Fields of papers citing papers by Junfeng Qu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 23 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mining high utility itemsets without candidate generation
Hit paper breakdown →
2012430
2 202321
3 202018
4 200616
5 202012
6 20226
7 20165
8 20104
9 20074
10 20244
11 20213
12 20183
13 20202
14 20142
15 20202
16
Time Series Similarity Matching with a New Distance Measure.
20071
17
Mining Structural Changes in Financial Time Series with Gray System.
20051
18
New Algorithm for Solving Shortest Path of Maze Problem
20061
19
Knowledge Retrieval in Financial Domain.
20081
20
PaperGuard: A Support Vector Machine Approach for Screening Machine Generated Papers.
20091

About Junfeng Qu

Junfeng Qu is a scholar working on Signal Processing, Computational Theory and Mathematics, Information Systems, Artificial Intelligence and Management Science and Operations Research, having authored 23 papers that have together received 540 indexed citations. Recurring topics across this work include Data Management and Algorithms (7 papers), Data Mining Algorithms and Applications (6 papers), Rough Sets and Fuzzy Logic (6 papers), Time Series Analysis and Forecasting (4 papers), Artificial Intelligence in Games (2 papers), Digital Games and Media (2 papers), Gene expression and cancer classification (2 papers) and Software Engineering and Design Patterns (2 papers). The work is most often cited by research in Computational Theory and Mathematics (349 citations), Information Systems (477 citations), Signal Processing (163 citations), Artificial Intelligence (268 citations) and Marketing (35 citations). Junfeng Qu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Mengchi Liu, Bo Hang, Philippe Fournier‐Viger, Chunyang Hu, Bo Tang, Jiaxing Zhang, Feng Sun, Haiming Wang, Lee H. Pratt and Qiong Gu. Their work appears in journals such as IEEE Access, Applied Intelligence, Computers in Biology and Medicine, Knowledge-Based Systems and IEEE Transactions on Knowledge and Data Engineering.

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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