Computer Science Review

Top Research Topics at Computer Science Review?

The journal is organized to address concerns in the fields of Artificial intelligence, Computer security, Data science, Field (computer science) and Theoretical computer science. The work on Artificial intelligence tackled in it brings together disciplines like Algorithm, Machine learning and Computer vision. The research on Computer security tackled can also make contributions to studies in the areas of Software deployment and The Internet.

Data science study tackled is connected to the field of Context (language use).

• Artificial intelligence (16.32%)
• Computer security (12.76%)
• Data science (12.76%)

What are the most cited papers published in the journal?

• Survey: Reservoir computing approaches to recurrent neural network training (1516 citations)
• Survey: Graph clustering (1103 citations)
• Worst-case equilibria (571 citations)

Research areas of the most cited articles at Computer Science Review:

The most cited papers are mainly concerned with subjects like Artificial intelligence, Theoretical computer science, Machine learning, Data science and Context (language use). While Artificial intelligence is the focus of the journal articles, it also provides insights into the studies of Sampling (statistics), Field (computer science) and Simulation. The journal publications focus on Machine learning research which is adjacent to topics in Software engineering.

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

• Artificial intelligence
• Operating system
• The Internet

The previous edition focused in particular on these issues:

Computer Science Review facilitates discussions on Field (computer science), Artificial intelligence, Data science, Computer security and Systematic review. The journal holds forums on Field (computer science) that merges themes from other disciplines such as Data mining, Biometrics, Wireless sensor network, Modality (human–computer interaction) and The Internet. The studies in Artificial intelligence featured incorporate elements of Algorithm and Machine learning.

The study on Machine learning presented in the journal intersects with subjects under the field of Scalability. It tackles studies in Context (language use) and the interrelated subject of Task (project management) to gain insights into Data science. While the primary focus in it is Computer security, it also dissects topics surrounding Software deployment and Cloud computing as a whole.

The most cited articles from the last journal are:

• Big data and IoT-based applications in smart environments: A systematic review (47 citations)
• A survey on deep learning and its applications (22 citations)
• Deep Learning Algorithms for Cybersecurity Applications: A Technological and Status Review (17 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.

Top authors and change over time

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

• Paul G. Spirakis (10 papers) published 2 papers at the last edition,
• Feng Xia (6 papers) absent at the last edition,
• Thierry Bouwmans (6 papers) absent at the last edition,
• Josep Díaz (5 papers) published 1 paper at the last edition,
• Ioannis Chatzigiannakis (5 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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

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

• Research Academic Computer Technology Institute (13 papers) published 1 paper at the last edition,
• Polytechnic University of Catalonia (11 papers) published 6 papers at the last edition,
• Charles University in Prague (11 papers) published 1 paper at the last edition,
• National and Kapodistrian University of Athens (8 papers) absent at the last edition,
• Dalian University of Technology (7 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, 6.74% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 18.07% were posted by at least one author from the top 10 institutions publishing in the journal. Another 8.43% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 25.30% of all publications and 48.19% 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 and Progression in Computer Science Research

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