| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 170 | 324 | 402 | 29 |
The journal is organized to address concerns in the fields of Artificial intelligence, Data mining, Machine learning, Distributed computing and Pattern recognition. The journal focuses on Artificial intelligence but the discussions also offer insight into other areas such as Computer vision and Natural language processing. Discussions in the journal are anchored in the subject of Distributed computing and the similar topic of Cloud computing.
The most cited papers are organized to address concerns in the fields of Artificial intelligence, Machine learning, Data science, Theoretical computer science and Mathematical optimization. While Artificial intelligence is the focus of the published articles, it also provides insights into the studies of Natural language processing, Computer vision and Pattern recognition. The studies on Data science discussed at the journal publications can also contribute to research in the domains of Empirical research and World Wide Web.
Frontiers of Computer Science covers a variety of subjects, including Artificial intelligence, Scheme (programming language), Machine learning, Theoretical computer science and Key (cryptography). It holds forums on Artificial intelligence that merges themes from other disciplines such as Relation (database), Heuristics and Natural language processing. Topics in Scheme (programming language) were tackled in line with various other fields like Computer network and Privacy preserving.
In addition to Machine learning research, it aims to explore topics under Adversarial system and Generative grammar. Frontiers of Computer Science tackles studies in Order (business) and the interrelated subject of Encryption to gain insights into Theoretical computer science. The concepts on Key (cryptography) presented in it can also apply to other research fields, including Fuse (electrical), Sentiment analysis, Complement (set theory) and Computer engineering.
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 Frontiers of Computer Science (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 Frontiers of Computer Science (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 2022 edition, 77.42% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 14.29% were posted by at least one author from the top 10 institutions publishing in the journal. Another 28.57% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 28.57% of all publications and 28.57% 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.
For inspired students who wish to contribute to these research topics in computer science as a future educator, understanding the pathway towards becoming a teaching professional is critical. Obtaining a degree in the field is often the first step, but there's more to it than that. Students must also go through appropriate teacher training, licensing processes, and other necessary education pathways that may vary by state. For instance, if a student is based in Pennsylvania and aspires to become a computer science teacher, they have to follow the state-specific guidelines and requirements. By so doing, these individuals can particularly obtain the needed skills and knowledge to impact future generations of computer science professionals and researchers. For a comprehensive guide on the process to follow, please find details on how to become a teacher in Pennsylvania. By following these insights, you'll be well-equipped to shape a future where Artificial Intelligence, Data Mining, Machine Learning, and other computer science fields are driven by competent and well-informed professionals. Apart from empowering you to be a change agent in the world of academia, these guidelines will also place you in a strong position to develop revolutionary papers that could dominate academic citations in the future. By stepping into the world of teaching, you are not just passing on knowledge, but also building the next frontier in computer science research.
Xibin Dong;Zhiwen Yu;Wenming Cao;Yifan Shi
(2020)Unknown
(2024)Zeli Wang;Hai Jin;Weiqi Dai;Kim-Kwang Raymond Choo
(2021)Unknown
(2021)Juntao Chen;Quan Zou;Quan Zou;Jing Li
(2022)Neng Hou;Neng Hou;Fazhi He;Yi Zhou;Yilin Chen
(2020)Yaopeng Liu;Hao Peng;Jianxin Li;Yangqiu Song
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