Gao Cong

16.8k citations
297 papers · 10.8k indexed · 8 hit papers · h-index 53

Gao Cong

281 papers receiving 10.5k citations

Hit Papers

Explorin...612009202620142020100200300400500

Peers

Gao Cong
Comparison fields: 5 of 163
  • Transportation 2.8k
  • Signal Processing 4.1k
  • Geography, Planning and Development 1.6k
  • Information Systems 4.1k
  • Computational Mathematics 100
Replace Wang-Chien Lee with:
Wang-Chien Lee United States
Wei‐Ying Ma China
Hongzhi Yin Australia
Kai Zheng China
Kian‐Lee Tan Singapore
Aixin Sun Singapore
Yannis Manolopoulos Greece
Chao Zhang China
Dik Lun Lee Hong Kong
Nicholas Jing Yuan China
Gao Cong relative to Wang-Chien Lee United States Wang-Chien Lee's profile →
Citations per field
00.5×5.8×
Wang-Chien Lee · 1×
Citations per year

Countries citing papers authored by Gao Cong

Since Specialization
Citations

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

Fields of papers citing papers by Gao Cong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20257
2 20254
3 20251
4 20251
5 20258
6 20247
7 202412
8 20241
9 20244
10 20240
11
Exploring Progress in Multivariate Time Series Forecasting: Comprehensive Benchmarking and Heterogeneity Analysisbreakdown →
202461
12 20248
13 202416
14
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)breakdown →
202445
15 20241
16 20241
17 20211
18
Towards Fine-Grained Compiler Identification with Neural Modeling.
20201
19
Exploiting Repeated Behavior Pattern and Long-term Item dependency for Session-based Recommendation.
20203
20 201852

About Gao Cong

Gao Cong is a scholar working on Signal Processing, Geography, Planning and Development and Transportation, having authored 297 papers that have together received 10.8k indexed citations. Recurring topics across this work include Data Management and Algorithms (106 papers), Advanced Database Systems and Queries (44 papers), Geographic Information Systems Studies (43 papers), Human Mobility and Location-Based Analysis (40 papers), Recommender Systems and Techniques (32 papers), Topic Modeling (29 papers), Data Mining Algorithms and Applications (28 papers) and Time Series Analysis and Forecasting (22 papers). The work is most often cited by research in Transportation (2.8k citations), Signal Processing (4.1k citations) and Geography, Planning and Development (1.6k citations). Gao Cong has collaborated with scholars based in Singapore, China and United States. Frequent co-authors include Christian S. Jensen, Quan Yuan, Aixin Sun, Xin Cao, Dingming Wu, Zongyang Ma, Lisi Chen, Xiucheng Li, Tuan-Anh Nguyen Pham and Nadia Magnenat‐Thalmann. Their work appears in journals such as Proceedings of the VLDB Endowment, IEEE Transactions on Knowledge and Data Engineering, The VLDB Journal, ACM Transactions on Information Systems and ACM Transactions on Database 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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