| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 705 | 23 | 23 | 7 |
The journal investigates areas of study like Artificial intelligence, Machine learning, Theoretical computer science, Algorithm and Programming language. The work on Artificial intelligence tackled in it brings together disciplines like Domain (software engineering), Context (language use), Data mining and Natural language processing.
The journal publications are organized to address concerns in the fields of Artificial intelligence, Machine learning, Algorithm, Knowledge management and World Wide Web. The most cited publications hold forums on Artificial intelligence that merge themes from other disciplines such as Natural language processing and Pattern recognition. Intelligent decision support system, Multi-agent system and Decision support system are some topics wherein Knowledge management research discussed in the published articles has an impact.
Artificial intelligence, Knowledge management, Reinforcement learning, Algorithm and Vehicle routing problem are the subjects of interest in the journal. In addition to Artificial intelligence research, Ai Communications aims to explore topics under Machine learning, Computer vision and Identification (information). The research on Reinforcement learning featured in it combines topics in other fields like Linear function, Control (management) and Rule-based system.
Topics in Algorithm explored in the journal were investigated in conjunction with research in Basis function, Traffic signal, Stochastic gradient descent and Cluster analysis. The concepts on Vehicle routing problem presented in Ai Communications can also apply to other research fields, including Multi-agent system, Scalability and Adaptation (computer science). Multi-agent system research in it involves the investigation of Dynamic problem studies, all of which are linked to disciplines such as Assignment problem, Context (language use), Arc routing, Distributed computing and Combinatorial auction.
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 Ai Communications (based on the number of publications) are:
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 Ai Communications (based on the number of publications) are:
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.
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, 0.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 0.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 0.00% of all publications and 100.00% were from other institutions.
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.
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.
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:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
With a degree or expertise in AI-related research topics, many individuals could easily ascend to becoming exemplary history educators, especially in a technologically-driven modern world. These professionals armed with the knowledge of AI can offer a unique advantage in teaching and research by implementing new strategies for educational purposes.
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Kamruzzaman Sarker;Lu Zhou;Aaron Eberhart;Pascal Hitzler
(2021)Marcella Cornia;Lorenzo Baraldi;Rita Cucchiara
(2021)Geoff Sutcliffe
(2020)Pedro M. Fernandes;Francisco C. Santos;Manuel Lopes
(2020)Theresa Ziemke;Lucas Nunes Alegre;Ana L. C. Bazzan
(2021)Exploring online degrees related to Computer Science can open diverse career opportunities. For those interested in blending technology with innovation, an applied artificial intelligence degree prepares students for roles in machine learning, data analysis, and automation across various industries.
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