Jih-Jie Chang

4.9k total citations · 1 hit paper
6 papers, 3.3k citations indexed

About

Jih-Jie Chang is a scholar working on Artificial Intelligence, Experimental and Cognitive Psychology and Computational Mathematics. According to data from OpenAlex, Jih-Jie Chang has authored 6 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 2 papers in Experimental and Cognitive Psychology and 1 paper in Computational Mathematics. Recurrent topics in Jih-Jie Chang's work include Visual and Cognitive Learning Processes (2 papers), Advanced Text Analysis Techniques (1 paper) and Reading and Literacy Development (1 paper). Jih-Jie Chang is often cited by papers focused on Visual and Cognitive Learning Processes (2 papers), Advanced Text Analysis Techniques (1 paper) and Reading and Literacy Development (1 paper). Jih-Jie Chang collaborates with scholars based in United States and Japan. Jih-Jie Chang's co-authors include J. Douglas Carroll, Roger N. Shepard, Christopher W. Tyler and Béla Julesz and has published in prestigious journals such as Journal of the Optical Society of America A, Psychometrika and Journal of Verbal Learning and Verbal Behavior.

In The Last Decade

Jih-Jie Chang

6 papers receiving 3.1k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Analysis of Individual Differences in Multidimensional Scaling Via an N-way Generalization of “Eckart-Young” Decomposition

1970 3.2k citations J. Douglas Carroll, Jih-Jie Chang Psychometrika profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Jih-Jie Chang United States	5	1.6k	684	536	477	364	6	3.3k
Jos M. F. ten Berge Netherlands	32	734 0.5×	457 0.7×	228 0.4×	286 0.6×	134 0.4×	107	4.0k
Morten Mørup Denmark	26	854 0.5×	545 0.8×	387 0.7×	470 1.0×	286 0.8×	123	3.1k
Yoshio Takane Canada	32	256 0.2×	345 0.5×	130 0.2×	612 1.3×	365 1.0×	137	5.1k
Anh Huy Phan Japan	23	2.4k 1.5×	1.4k 2.1×	1.2k 2.2×	845 1.8×	863 2.4×	100	5.4k
Peter H. Schönemann United States	22	123 0.1×	213 0.3×	205 0.4×	613 1.3×	614 1.7×	57	3.2k
Heinz Neudecker Netherlands	23	169 0.1×	423 0.6×	259 0.5×	574 1.2×	249 0.7×	123	4.4k
Daniel Hsu United States	30	356 0.2×	342 0.5×	495 0.9×	2.2k 4.5×	703 1.9×	86	4.0k
Sham M. Kakade United States	41	376 0.2×	525 0.8×	673 1.3×	3.6k 7.5×	1.4k 3.8×	121	7.4k
Amy N. Langville United States	17	114 0.1×	472 0.7×	204 0.4×	912 1.9×	531 1.5×	37	3.8k
V. Paúl Pauca United States	19	118 0.1×	545 0.8×	386 0.7×	534 1.1×	895 2.5×	44	2.7k

Countries citing papers authored by Jih-Jie Chang

Since Specialization

Citations

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

Fields of papers citing papers by Jih-Jie Chang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jih-Jie Chang. 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 Jih-Jie Chang. The network helps show where Jih-Jie Chang may publish in the future.

Co-authorship network of co-authors of Jih-Jie Chang

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

All Works

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6 of 6 papers shown

1.

Julesz, Béla & Jih-Jie Chang. (1980). Disparity limits for random-dot cinematograms for movement and form detection, and a learning effect (A). Journal of the Optical Society of America A. 70. 1624. 1 indexed citations

2.

Tyler, Christopher W. & Jih-Jie Chang. (1976). <title>Visual Processing Of Repetitive Images</title>. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 74. 216–224. 4 indexed citations

3.

Carroll, J. Douglas & Jih-Jie Chang. (1970). Analysis of Individual Differences in Multidimensional Scaling Via an N-way Generalization of “Eckart-Young” Decomposition. Psychometrika. 35(3). 283–319. 3189 indexed citations breakdown →

4.

Chang, Jih-Jie & Roger N. Shepard. (1964). Meaningfulness in classification learning with pronounceable trigrams. Journal of Verbal Learning and Verbal Behavior. 3(1). 85–90. 6 indexed citations

5.

Shepard, Roger N. & Jih-Jie Chang. (1963). Stimulus generalization in the learning of classifications.. Journal of Experimental Psychology. 65(1). 94–102. 97 indexed citations

6.

Shepard, Roger N. & Jih-Jie Chang. (1963). Forced-choice tests of recognition memory under steady-state conditions. Journal of Verbal Learning and Verbal Behavior. 2(1). 93–101. 47 indexed citations

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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