Lin Deng

565 citations
12 papers · 428 · h-index 8

Impact in

    • Web Data Mining and Analysis
    • Recommender Systems and Techniques
    • Data Mining Algorithms and Applications

Papers in

    • Gene expression and cancer classification 3
    • Bioinformatics and Genomic Networks 2
    • Machine Learning in Bioinformatics 2
    • Web Data Mining and Analysis 3
    • Recommender Systems and Techniques 2
    • Information Retrieval and Search Behavior 2

Lin Deng

12 papers receiving 414 citations

Peers

Lin Deng
Comparison fields: 5 of 88
  • Information Systems 106
  • Neurology 30
  • Cellular and Molecular Neuroscience 65
  • Artificial Intelligence 125
  • Cognitive Neuroscience 53
Replace Dohoon Kim with:
Dohoon Kim South Korea
Ke Sun China
Gordon M. Shepherd United States
Xueqin Shen China
Christopher Wallace United Kingdom
Dũng H. Phan United States
Zhe Zhou China
Abul Kalam Al Azad Bangladesh
Lin Deng relative to Dohoon Kim South Korea Dohoon Kim's profile →
Citations per field
00.5×2×2.7×
Dohoon Kim · 1×
Citations per year

Countries citing papers authored by Lin Deng

Since Specialization
Citations

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

Fields of papers citing papers by Lin Deng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Lin Deng, 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 Lin Deng Line = papers co-authored together Lin Deng links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1 2014103
2 2005103
3 200462
4 200455
5 200531
6 200728
7 200424
8
Spying Out Real User Preferences for Metasearch Engine Personalization.
200410
9 20045
10 20174
11 20062
12 20251

About Lin Deng

Lin Deng is a scholar working on Molecular Biology, Information Systems, Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 428 indexed citations. Recurring topics across this work include Web Data Mining and Analysis (3 papers), Gene expression and cancer classification (3 papers), Bioinformatics and Genomic Networks (2 papers), Recommender Systems and Techniques (2 papers), Information Retrieval and Search Behavior (2 papers), Machine Learning in Bioinformatics (2 papers), Imbalanced Data Classification Techniques (1 paper) and Infrared Target Detection Methodologies (1 paper). The work is most often cited by research in Information Systems (106 citations), Neurology (30 citations), Cellular and Molecular Neuroscience (65 citations), Artificial Intelligence (125 citations) and Cognitive Neuroscience (53 citations). Lin Deng has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Dik Lun Lee, Xiaoyong Chai, Charles X. Ling, Qiang Yang, Jian Pei, Wilfred Ng, Gong Chen, Min Jiang, Jinwen Ma and Ian H. Stevenson. Their work appears in journals such as Computer Networks, Gene Therapy, ACM Transactions on Internet Technology, Molecular Biology of the Cell and Journal of Neuroscience.

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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