Sheng-Chieh Lin

1.1k total citations
28 papers, 498 citations indexed

About

Sheng-Chieh Lin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Astronomy and Astrophysics. According to data from OpenAlex, Sheng-Chieh Lin has authored 28 papers receiving a total of 498 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 3 papers in Astronomy and Astrophysics. Recurrent topics in Sheng-Chieh Lin's work include Topic Modeling (13 papers), Natural Language Processing Techniques (11 papers) and Multimodal Machine Learning Applications (7 papers). Sheng-Chieh Lin is often cited by papers focused on Topic Modeling (13 papers), Natural Language Processing Techniques (11 papers) and Multimodal Machine Learning Applications (7 papers). Sheng-Chieh Lin collaborates with scholars based in Canada, Taiwan and United States. Sheng-Chieh Lin's co-authors include Jimmy Lin, Jheng-Hong Yang, Rodrigo Nogueira, Xueguang Ma, Ronak Pradeep, Ruidong Zhu, Sanghun Choi, Jiun‐Haw Lee, Shin‐Tson Wu and Guanjun Tan and has published in prestigious journals such as The Astrophysical Journal, Monthly Notices of the Royal Astronomical Society and Optics Express.

In The Last Decade

Sheng-Chieh Lin

24 papers receiving 465 citations

Peers

Sheng-Chieh Lin
Comparison fields: 5 of 57
  • Artificial Intelligence 335
  • Computer Vision and Pattern Recognition 138
  • Information Systems 106
  • Astronomy and Astrophysics 57
  • Electrical and Electronic Engineering 51
Replace W. Gässler with:
W. Gässler Germany
Junchen Wan China
Christopher Wolf United States
Michael Petrov Russia
P. K. Srijith India
Thomas Uram United States
Antonio Messina Italy
Nuno Cardoso Portugal
Muhammad Aqib Javed Pakistan
W. Gässler Germany View profile →
Citations per field, relative to Sheng-Chieh Lin
Sheng-Chieh Lin · 1×
Citations per year, relative to Sheng-Chieh Lin
Sheng-Chieh Lin · 1×

Countries citing papers authored by Sheng-Chieh Lin

Since Specialization
Citations

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

Fields of papers citing papers by Sheng-Chieh Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sheng-Chieh Lin. 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 Sheng-Chieh Lin. The network helps show where Sheng-Chieh Lin may publish in the future.

Co-authorship network of co-authors of Sheng-Chieh Lin

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng-Chieh Lin. A scholar is included among the top collaborators of Sheng-Chieh Lin 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 Sheng-Chieh Lin. Sheng-Chieh Lin 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
# Work Indexed citations
1 4
2 2
3 13
4 3
5 0
6 4
7 8
8 4
9 10
10 79
11 27
12 33
13
TREC 2020 Notebook: CAsT Track.
2
14 5
15
Query and Answer Expansion from Conversation History.
5
16
Negative-Aware Collaborative Filtering.
1
17 2
18 21
19 5
20 3

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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