Xiaoying Gao

2.3k citations
93 papers · 1.4k indexed · h-index 19
Topics
Evolutionary Algorithms and Applications (15 papers)Web Data Mining and Analysis (15 papers)Text and Document Classification Technologies (15 papers)

In The Last Decade

Xiaoying Gao

85 papers receiving 1.3k citations

Peers

Xiaoying Gao
Comparison fields: 5 of 143
  • Artificial Intelligence 421
  • Molecular Biology 389
  • Radiology, Nuclear Medicine and Imaging 239
  • Information Systems 195
  • Neurology 162
Replace Fen Xia with:
Fen Xia United States
Dan Massey United States
Ji Zhang China
Ευγενία Γιαννοπούλου United States
Yuichi Kaji Japan
Pengyi Yang Australia
P. K. Vinod India
Alexander Aliper Russia
Hyunjung Shin South Korea
Kun Zhang United States
Xiaoying Gao relative to Fen Xia United States Fen Xia's profile →
Citations per field
00.5×3.8×
Fen Xia · 1×
Citations per year

Countries citing papers authored by Xiaoying Gao

Since Specialization
Citations

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

Fields of papers citing papers by Xiaoying Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaoying Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaoying Gao. A scholar is included among the top collaborators of Xiaoying Gao 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 Xiaoying Gao. Xiaoying Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 0
3 10
4 0
5 9
6 9
7 24
8 5
9 15
10 46
11 27
12 1
13 197
14
Anatomy of drive-by download attack
19
15 101
16 3
17 88
18
Semi-Structured Data Extraction from Heterogeneous Sources
1
19 51
20 1

About Xiaoying Gao

Xiaoying Gao is a scholar working on Artificial Intelligence, Information Systems and Signal Processing, having authored 93 papers that have together received 1.4k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (15 papers), Web Data Mining and Analysis (15 papers) and Text and Document Classification Technologies (15 papers). The work is most often cited by research in Neurology (162 citations), Artificial Intelligence (421 citations) and Radiology, Nuclear Medicine and Imaging (239 citations). Xiaoying Gao has collaborated with scholars based in New Zealand, China and United States. Frequent co-authors include Peter Andreae, Bing Xue, Ian Welch, Mengjie Zhang, Daniel R. Crabtree, Jinyan Li, Zhihua Qiu, Bernardino Ghetti, Ana G. Barbeito and Martín A. Baraibar. Their work appears in journals such as Neuron, Journal of Neuroscience and Analytical Chemistry.

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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