| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 113 | 238 | 265 | 39 |
The primary areas of discussion in Artificial Intelligence are Artificial intelligence, Theoretical computer science, Algorithm, Mathematical optimization and Machine learning. It explores issues in Artificial intelligence which can be linked to other research areas like Task (project management) and Natural language processing.
The journal publications are organized to reinforce research efforts on Artificial intelligence, Theoretical computer science, Algorithm, Mathematical optimization and Machine learning. The works on Artificial intelligence tackled in the journal papers bring together disciplines like Mathematical economics and Natural language processing. While work presented in the published articles provide substantial information on Mathematical optimization, it also covers topics in Constraint satisfaction and Constraint satisfaction problem.
The topics of Set (abstract data type), Artificial intelligence, Mathematical optimization, Constraint (information theory) and Process (engineering) are the focal point of discussions in Artificial Intelligence. While Set (abstract data type) is the focus of Artificial Intelligence, it also provided insights into the studies of Algorithm, Transferable utility, Curse of dimensionality and Manifold. Some problems in Artificial intelligence that were presented in it overlapped with concepts under Differentiable function, Machine learning and Performance improvement.
The research on Constraint (information theory) tackled can also make contributions to studies in the areas of Resource allocation, Arithmetic, Scheduling (computing), Variety (universal algebra) and Solver. Process (engineering) research in Artificial Intelligence involves the investigation of Product (business) studies, all of which are linked to disciplines such as Representation (mathematics). In it, Feature (computer vision), Factorization, Field (computer science), Selection (genetic algorithm) and Range (mathematics) are investigated in conjunction with one another to address concerns in Inference 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 Artificial Intelligence (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 Artificial Intelligence (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, 23.08% 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 10.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 10.00% of all publications and 80.00% 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.
The world of artificial intelligence offers many exciting career opportunities. From research scientists and AI engineers to data scientists - the field is vast and growing. Many professionals also choose to specialize in a specific area of AI, such as machine learning or natural language processing. Education in computer science, mathematics, and statistics can form a foundation for a career in AI. Furthermore, an understanding of AI principles and technologies are essential. Various education paths can lead to a career in AI, be it a bachelor's degree with relevant experience, or advanced degrees such as a masters or doctoral degree. An example of such a career path can be found in our article on how to become a middle school math teacher in Ohio. Many universities, colleges, and private institutions offer artificial intelligence programs. Some even offer online programs, making education in AI more accessible than ever. But education is just one part of the equation. The other is the right mindset - AI professionals are expected to be creative and innovative, capable of thinking out-of-the-box to solve complex problems. There is a high demand for AI professionals worldwide. They can work in various sectors including technology, finance, healthcare, transportation, and even education. From developing intelligent systems to improving existing ones, the opportunities are endless for those in the AI field. Remember - continuous learning is key to succeeding in AI. The field is always evolving, so it's crucial to keep up-to-date with the latest trends, technologies, and research.
Wenhan Luo;Wenhan Luo;Junliang Xing;Anton Milan;Xiaoqin Zhang
(2021)Markus Langer;Daniel Oster;Timo Speith;Holger Hermanns
(2021)David Silver;Satinder P. Singh;Doina Precup;Richard S. Sutton
(2021)Jasper van der Waa;Elisabeth Nieuwburg;Anita H. M. Cremers;Mark A. Neerincx
(2021)Nolan Bard;Jakob N. Foerster;Sarath Chandar;Neil Burch
(2020)Eoin M. Kenny;Courtney Ford;Molly S. Quinn;Mark T. Keane
(2021)Katie Atkinson;Trevor J. M. Bench-Capon;Danushka Bollegala
(2020)Simon Burton;Ibrahim Habli;Tom Lawton;John McDermid
(2020)Samy Badreddine;Artur d'Avila Garcez;Luciano Serafini;Michael Spranger
(2020)Robin Manhaeve;Sebastijan Dumančić;Angelika Kimmig;Thomas Demeester
(2021)Pursuing a Computer Science degree online offers flexibility and access to various learning formats. Many students prefer self paced college courses, allowing them to balance studies with work or personal commitments. This approach is ideal for those who need to progress at their own speed without fixed schedules.
Cost is another critical consideration. Numerous institutions provide online affordable master's programs that deliver advanced skills without burdening students with excessive debt. These programs enable career advancement in specialized fields such as cybersecurity, data science, or software engineering.
For those starting out or seeking quicker entry into the tech industry, exploring what's the easiest associate's degree to get can be a strategic choice. Associate degrees in computer science or related areas provide foundational knowledge and can lead to well-paying jobs or transfer opportunities to four-year programs.
It's essential to choose programs from nationally accredited online colleges to ensure the education meets industry standards and employers recognize the degree. Accreditation also affects eligibility for financial aid and professional certifications.
