Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Convolutional Matrix Factorization for Document Context-Aware Recommendation
Citations per year, relative to Sungyoung Lee Sungyoung Lee (= 1×)
peers
Mohamed Elhoseny
Countries citing papers authored by Sungyoung Lee
Since
Specialization
Citations
This map shows the geographic impact of Sungyoung Lee'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 Sungyoung Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sungyoung Lee more than expected).
This network shows the impact of papers produced by Sungyoung Lee. 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 Sungyoung Lee. The network helps show where Sungyoung Lee may publish in the future.
Co-authorship network of co-authors of Sungyoung Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Sungyoung Lee.
A scholar is included among the top collaborators of Sungyoung Lee 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 Sungyoung Lee. Sungyoung Lee is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Lee, Sungyoung, et al.. (2014). Call Speech Emotion Recognition for Emotion based Services. Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong. 41(3). 208–213.4 indexed citations
8.
Kim, Hyunwoo & Sungyoung Lee. (2013). The Phoneme Kernel Technique based on Support Vector Machine for Emotion Classification of Mobile Texts). Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong. 40(6). 350–355.5 indexed citations
9.
Qaisar, Saad, et al.. (2013). A hidden Markov model for detection and classification of arm action in cricket using wearable sensors. Journal of Multimedia. 9(1). 128–144.3 indexed citations
10.
Khattak, Asad Masood, Rabia Batool, Zeeshan Pervez, Adil Khan, & Sungyoung Lee. (2013). Ontology Evolution and Challenges. Journal of information science and engineering. 29(5). 851–871.19 indexed citations
11.
Han, Manhyung & Sungyoung Lee. (2013). Personalized Activity Modeling and Real-time Activity Recognition based on Smartphone Multimodal Sensors. Jeongbo gwahaghoe nonmunji. so'peuteuweeo mich eung'yong. 40(6). 332–341.2 indexed citations
12.
Khan, Wajahat Ali, et al.. (2012). Towards personalized health profiling in social network. 760–765.6 indexed citations
Lee, Sungyoung, et al.. (2011). Preface for the Special Issue on uHealthcare. Journal of Computing Science and Engineering. 5(3). 236–236.5 indexed citations
15.
Amin, Muhammad Bilal, Wajahat Ali Khan, Sungyoung Lee, & Young-Koo Lee. (2011). Cloud Computing for Healthcare IT Infrastructure. 한국정보과학회 학술발표논문집. 38. 112–115.
16.
Khattak, Asad Masood, et al.. (2010). Analyzing Association Rule Mining and Clustering on Sales Day Data with XLMiner and Weka. International Journal of Database Theory and Application. 3(1). 13–22.7 indexed citations
17.
Lee, Sungyoung, et al.. (2009). Modified SHA-1 hash function (mSHA-1). ITC-CSCC :International Technical Conference on Circuits Systems, Computers and Communications. 1320–1323.5 indexed citations
18.
d’Auriol, Brian J., et al.. (2008). Viewer Perception of Superellipsoid-based Accelerometer Visualization Techniques.. 129–135.1 indexed citations
19.
Guan, Donghai, А. В. Гаврилов, Weiwei Yuan, Young-Koo Lee, & Sungyoung Lee. (2007). A Novel Hybrid Neural Network for Data Clustering.. 284–288.1 indexed citations
20.
Khan, Mohammad A. U., et al.. (2007). Vessel Enhancement in Angiography Images using Decimation-Free Directional Filter Bank.. IPCV. 175–181.1 indexed citations
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.