Jae‐wook Ahn

973 citations
34 papers · 525 indexed · h-index 12

Impact in

Papers in

Jae‐wook Ahn

33 papers receiving 488 citations

Peers

Jae‐wook Ahn
Comparison fields: 5 of 56
  • Computer Science Applications 68
  • Information Systems 278
  • Computer Vision and Pattern Recognition 233
  • Artificial Intelligence 186
  • Information Systems and Management 38
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Citations per year

Countries citing papers authored by Jae‐wook Ahn

Since Specialization
Citations

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

Fields of papers citing papers by Jae‐wook Ahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jae‐wook Ahn. 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 Jae‐wook Ahn. The network helps show where Jae‐wook Ahn may publish in the future.

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20194
3 20192
4
A DDC visual interface for metadata exploration
20152
5 20159
6 201511
7
Mysterious Influential Users in Political Communication on Twitter: Users’ Occupation Information and Its Impact on Retweetability
20151
8 201380
9 20113
10 201113
11
Analyzing User Behavior Patterns in Adaptive Exploratory Search Systems with LifeFlow
20112
12
Teaching Information Retrieval With Web-based Interactive Visualization
20106
13 20101
14 201012
15 20082
16 200723
17 20077
18
QuizVIBE: Accessing Educational Objects with Adaptive Relevance-Based Visualization
20064
19 200619
20
Pitt at TREC 2005: HARD and Enterprise
20051

About Jae‐wook Ahn

Jae‐wook Ahn is a scholar working on Computer Science Applications, Information Systems, Computer Vision and Pattern Recognition, Information Systems and Management and Artificial Intelligence, having authored 34 papers that have together received 525 indexed citations. Recurring topics across this work include Data Visualization and Analytics (9 papers), Information Retrieval and Search Behavior (8 papers), Semantic Web and Ontologies (7 papers), Recommender Systems and Techniques (7 papers), Topic Modeling (5 papers), Web Data Mining and Analysis (5 papers), Advanced Database Systems and Queries (4 papers) and Open Education and E-Learning (4 papers). The work is most often cited by research in Computer Science Applications (68 citations), Information Systems (278 citations), Computer Vision and Pattern Recognition (233 citations), Artificial Intelligence (186 citations) and Information Systems and Management (38 citations). Jae‐wook Ahn has collaborated with scholars based in United States, United Kingdom and Chile. Frequent co-authors include Peter Brusilovsky, Daqing He, Jonathan Grady, Catherine Plaisant, Ben Shneiderman, Sue Yeon Syn, Rosta Farzan, Qi Li, Michael Yudelson and Radu Florian. Their work appears in journals such as Information Processing & Management, Information Visualization, International Journal on Digital Libraries, IEEE Transactions on Visualization and Computer Graphics and Proceedings of the American Society for Information Science and Technology.

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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