Si Shen

864 citations
52 papers · 563 indexed · h-index 14

Impact in

Papers in

Si Shen

46 papers receiving 540 citations

Peers

Si Shen
Comparison fields: 5 of 126
  • Statistics, Probability and Uncertainty 68
  • Information Systems 111
  • Artificial Intelligence 148
  • Transportation 30
  • Pharmaceutical Science 21
Replace Xiaodong Feng with:
Xiaodong Feng China
Wanru Wang China
Şule Gündüz Öğüdücü Türkiye
Seungwoo Lee South Korea
Chintan Amrit Netherlands
Dhanya Pramod India
Héctor G. Ceballos Mexico
Vera Miguéis Portugal
Lixin Zhou China
Qingxing Dong China
Si Shen relative to Xiaodong Feng China Xiaodong Feng's profile →
Citations per field
00.5×1.5×1.9×
Xiaodong Feng · 1×
Citations per year

Countries citing papers authored by Si Shen

Since Specialization
Citations

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

Fields of papers citing papers by Si Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20259
2 20241
3 20244
4 20240
5 202420
6 20249
7 202316
8 20232
9 20235
10 20230
11 202310
12 20224
13 20210
14
Research on Software Entity Extraction and Analysis Based on Deep Learning.
20191
15
Research on Functional Structure Identification of Academic Text Based on Deep Learning.
20192
16 20194
17 20153
18
An Overview of Mobile E-Library Development at Home and Abroad
20130
19 20111
20 200919

About Si Shen

Si Shen is a scholar working on Pharmaceutical Science, Statistics, Probability and Uncertainty, Artificial Intelligence, Dermatology and Transportation, having authored 52 papers that have together received 563 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Advanced Text Analysis Techniques (5 papers), Advancements in Transdermal Drug Delivery (4 papers), scientometrics and bibliometrics research (4 papers), Sentiment Analysis and Opinion Mining (3 papers), Traffic Prediction and Management Techniques (3 papers), Natural Language Processing Techniques (3 papers) and Biomedical Text Mining and Ontologies (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (68 citations), Information Systems (111 citations), Artificial Intelligence (148 citations), Transportation (30 citations) and Pharmaceutical Science (21 citations). Si Shen has collaborated with scholars based in China, United States and Belgium. Frequent co-authors include Dongbo Wang, Xiaotong Li, Peng Wu, Xinning Su, Weizhu Chen, Daqing He, Qiang Yang, Botao Amber Hu, Ronald Rousseau and Xiaoyan Li. Their work appears in journals such as Scientometrics, IEEE Access, The Electronic Library, Atmospheric and Oceanic Science Letters and International Journal of Information Management.

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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