| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1103 | 4 | 5 | 2 |
The journal is mainly concerned with subjects like Artificial intelligence, Algorithm, Computer network, Data mining and Distributed computing. Natural language processing, Machine learning, Computer vision and Pattern recognition are some topics wherein Artificial intelligence research discussed in Computer Science have an impact. It investigates Pattern recognition research which frequently intersects with Feature (computer vision).
The research on Algorithm featured in Computer Science combines topics in other fields like Theoretical computer science and Mathematical optimization. The Computer network works featured in the journal incorporate elements from Wireless and Computer security. The Data mining study featured in the journal draws connections with the study of Cluster analysis.
Many of the studies tackled connect Wireless sensor network with a similar field of study like Key distribution in wireless sensor networks.
The most cited publications focus largely on the fields of Artificial intelligence, Algorithm, Mathematical optimization, Theoretical computer science and Distributed computing. While work presented in the most cited papers provide substantial information on Artificial intelligence, it also covers topics in Field (computer science), Data mining and Pattern recognition. The published papers explore issues in Mathematical optimization which can be linked to other research areas like Set (abstract data type) and Benchmark (computing).
The journal mostly deals with topics like Humanities, Artificial intelligence, Library science, Gynecology and Natural language processing. In the journal, Machine learning and Pattern recognition are investigated in conjunction with one another to address concerns in Artificial intelligence research.
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 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 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 2021 edition, 84.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 16.67% 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 83.33% 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.
As computer science continues to evolve and advance, the potential usage of its various technologies in other fields such as education is notable. The application of these developing technologies can potentially make learning more efficient and easier for both teachers and students. Notably, a prime area of application is in teacher training and development specifically in the context of obtaining credentials for the teaching profession. In North Carolina, for example, obtaining a teaching credential can be a convoluted process and integrating Ceomputer Science technologies could simplify the procedure. Computer Science technologies could be used to develop systems and platforms that provide clear and straightforward information about credential programs, potentially even offering online courses or similar learning resources. To exemplify, consider an Artificial Intelligence-powered portal that provides comprehensive details about the teaching credential programs in North Carolina. Future educators can easily acquire information about the various programs available, their respective costs, duration and other pertinent details, all in a single and accessible platform. This type of advancement in education can pave the way for a more efficient and effective education system, not just in North Carolina, but everywhere else. As these technologies continue to improve, we can expect them to contribute even more to various disciplines, including education.
Benyamin Ahmadnia;Bonnie J. Dorr;Parisa Kordjamshidi
(2020)Hakan Çakar;Abdulkadir Sengur
(2021)For students interested in studying Computer Science in the USA, exploring related online degree options can open doors to diverse career paths. Many aspiring engineers choose to enroll in online colleges for engineering, which offer flexible programs that combine theory and practical skills across various disciplines.
Those passionate about creativity and technology might consider a game design degree. This pathway merges computer science principles with artistic development, preparing graduates for roles in the booming gaming industry.
Security concerns have made cybersecurity one of the fastest-growing fields. Pursuing an accredited online cyber security degree ensures students gain essential skills to protect data and infrastructure from emerging threats.
Data-driven decision making fuels many industries today, making data science degrees highly valuable. These programs equip learners with tools to analyze and interpret complex datasets, fueling innovation and strategic growth.
