Ruoxi Wang

1.5k citations
26 papers · 906 indexed · 1 hit paper · h-index 11

Ruoxi Wang

25 papers receiving 872 citations

Hit Papers

Deep & Cross Network for Ad Click Predictions6412017202620202023200400600

Peers

Ruoxi Wang
Comparison fields: 5 of 107
  • Information Systems 481
  • Artificial Intelligence 413
  • Computer Vision and Pattern Recognition 254
  • Management Science and Operations Research 96
  • Signal Processing 78
Replace Yu-Chin Juan with:
Yu-Chin Juan Taiwan
Wei-Sheng Chin Taiwan
Zhiqiang Zhang China
Baolin Yi China
Qing Cui China
Binbin Zhang China
Ruozhou Yu United States
Yajun Du China
Ruoxi Wang relative to Yu-Chin Juan Taiwan Yu-Chin Juan's profile →
Citations per field
00.5×3.7×
Yu-Chin Juan · 1×
Citations per year

Countries citing papers authored by Ruoxi Wang

Since Specialization
Citations

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

Fields of papers citing papers by Ruoxi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202314
2 202310
3 20233
4 20231
5 202112
6 20219
7
DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems.
20205
8 20201
9 20206
10 202033
11 20195
12 201845
13 20183
14 201812
15 201814
16
Deep & Cross Network for Ad Click Predictionsbreakdown →
2017641
17 201635
18 201315
19 20058
20 20053

About Ruoxi Wang

Ruoxi Wang is a scholar working on Hardware and Architecture, Computer Networks and Communications and Artificial Intelligence, having authored 26 papers that have together received 906 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (8 papers), Anomaly Detection Techniques and Applications (5 papers), Catalytic C–H Functionalization Methods (3 papers), Graphene research and applications (2 papers), Radical Photochemical Reactions (2 papers), Boron and Carbon Nanomaterials Research (2 papers), Internet Traffic Analysis and Secure E-voting (2 papers) and Artificial Immune Systems Applications (2 papers). The work is most often cited by research in Information Systems (481 citations), Artificial Intelligence (413 citations) and Computer Vision and Pattern Recognition (254 citations). Ruoxi Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Bin Fu, Gang Fu, Mingliang Wang, Chengbu Liu, Lingyu Yan, Dongju Zhang, Zhiwei Ye, Chunzhi Wang, Ohyun Kwon and Feng Chen. Their work appears in journals such as Chemosphere, Sensors, International Journal of Web and Grid Services, EURASIP Journal on Wireless Communications and Networking and Chemical Physics Letters.

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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