World's Best Scientists 2026 revealed!
Connection Science
H-index 16

Connection Science

0954-0091

Published by: Taylor & Francis

https://www.tandfonline.com/toc/ccos20/current

Ranking & Metrics

Discipline name Position Best Scientists Publications D-Index
Computer Science 372 37 52 16

Additional Metrics

Number of Best Scientists*: 47
Documents by Best Scientists*: 60
Top 100 Ranked Scientists*: 0
SCIMAGO H-index: 52
SCIMAGO SJR: 0.681
Impact Factor: 3.4

Overview

Top Research Topics at Connection Science?

The primary areas of discussion in the journal are Artificial intelligence, Artificial neural network, Connectionism, Cognitive science and Robot. The research on Artificial intelligence featured in it combines topics in other fields like Natural language processing, Machine learning and Pattern recognition. Connection Science is focused mainly on Natural language processing, particularly Natural language.

The journal explores topics in Artificial neural network which can be helpful for research in disciplines like Algorithm and Generalization. The journal dives deep in exploring the relationship between the study of Connectionism and Knowledge representation and reasoning. In addition to Cognitive science research, it aims to explore topics under Cognition and Embodied cognition.

The Robot study tackled is a key component of adjacent topics in the area of Human–computer interaction.

  • Artificial intelligence (48.84%)
  • Artificial neural network (26.27%)
  • Connectionism (16.20%)

What are the most cited papers published in the journal?

  • Error Correlation and Error Reduction in Ensemble Classifiers (536 citations)
  • Developmental robotics: a survey (507 citations)
  • How to Do the Right Thing (483 citations)

Research areas of the most cited articles at Connection Science:

The published papers focus on Artificial intelligence, Artificial neural network, Connectionism, Robot and Machine learning. The published articles are focused mainly on Artificial intelligence, particularly Catastrophic interference. While the journal papers focused on Artificial neural network, they were also able to explore topics like Function (mathematics), Algorithm and Pattern recognition.

What topics the last edition of the journal is best known for?

  • Artificial intelligence
  • Law
  • Machine learning

The previous edition focused in particular on these issues:

The scientific interests tackled in Connection Science are Artificial intelligence, Computer network, Computer security, Algorithm and Cloud computing. While work presented in it provided substantial information on Artificial intelligence, it also covered topics in Machine learning, Computer vision and Pattern recognition. The majority of Machine learning studies are focused on the issues of Artificial neural network.

The studies in Computer network featured incorporate elements of Transmission (telecommunications) and Edge computing. The study on Computer security presented in the journal intersects with subjects under the field of Information technology. The work on Cloud computing tackled in the journal brings together disciplines like Distributed computing and Encryption.

The most cited articles from the last journal are:

  • Multi-Keyword ranked search based on mapping set matching in cloud ciphertext storage system (13 citations)
  • OAC-HAS: outsourced access control with hidden access structures in fog-enhanced IoT systems (9 citations)
  • A novel data representation framework based on nonnegative manifold regularisation (9 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

The top authors publishing in Connection Science (based on the number of publications) are:

  • Garrison W. Cottrell (13 papers) absent at the last edition,
  • Tom Ziemke (9 papers) absent at the last edition,
  • Stefano Nolfi (9 papers) absent at the last edition,
  • Wei Liang (8 papers) published 8 papers at the last edition,
  • Amanda J. C. Sharkey (8 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Only papers with recognized affiliations are considered

The top affiliations publishing in Connection Science (based on the number of publications) are:

  • Providence College (18 papers) published 18 papers at the last edition,
  • University of Sheffield (16 papers) absent at the last edition,
  • Indiana University (10 papers) absent at the last edition,
  • Hunan University (10 papers) published 10 papers at the last edition,
  • University of Hertfordshire (9 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 1.33% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 25.68% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.41% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 12.16% of all publications and 56.76% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

  • Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
  • Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
  • Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
  • Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
  • Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in Connection Science

In addition to providing comprehensive and detailed research insights in the fields of Artificial Intelligence, Connectionism and Cognitive Science, Connection Science widens the scope of career opportunities for its readers. The research knowledge gained in this field can leverage your skills in different teaching professions.

The state of Rhode Island, for instance, has numerous teaching credential programs that particularly focus on these areas of research. Whether you are looking to specialize in teaching Artificial Intelligence or intending to inspire young minds about the endless potential and scope of Connectionism. You may find best teaching credential programs in Rhode Island very helpful in your career planning.

Familiarity with the latest research articles published in the journal will certainly provide an edge in the competitive academic job market. Dive deep into these exhilarating fields of tech and make significant contributions to the world of academia.

Top Publications

  • Applications of federated learning in smart cities: recent advances, taxonomy, and open challenges

    (2021)
    138 Citations
  • Multi-Keyword ranked search based on mapping set matching in cloud ciphertext storage system

    Tingting Xiao;Dezhi Han;Junhui He;Kuan-Ching Li

    (2021)
    48 Citations
  • Effective classification of android malware families through dynamic features and neural networks

    Gianni D'Angelo;Francesco Palmieri;Antonio Robustelli;Arcangelo Castiglione

    (2021)
    36 Citations
  • A novel cluster head selection using Hybrid Artificial Bee Colony and Firefly Algorithm for network lifetime and stability in WSNs

    J. Sengathir;A. Rajesh;Gaurav Dhiman;S. Vimal

    (2021)
    31 Citations
  • The identification of influential nodes based on structure similarity

    Jie Zhao;Yutong Song;Fan Liu;Yong Deng

    (2021)
    31 Citations
  • A lightweight authentication scheme for telecare medical information system

    (2021)
    30 Citations
  • A Hybrid parallel deep learning model for efficient intrusion detection based on metric learning

    (2022)
    29 Citations
  • Graph learning-based spatial-temporal graph convolutional neural networks for traffic forecasting

    (2021)
    28 Citations
  • Selective transfer learning with adversarial training for stock movement prediction

    (2022)
    27 Citations
  • A novel image compression technology based on vector quantisation and linear regression prediction

    Shuying Xu;Chin-Chen Chang;Chin-Chen Chang;Yanjun Liu

    (2021)
    23 Citations

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