| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 146 | 209 | 225 | 32 |
The scientific interests tackled in Journal of Artificial Intelligence Research are Artificial intelligence, Theoretical computer science, Mathematical optimization, Algorithm and Machine learning. Journal of Artificial Intelligence Research centers on topics in Artificial intelligence, with a focus on Inference. The Theoretical computer science research dealing mostly with Description logic is the focus of Journal of Artificial Intelligence Research.
The study on Mathematical optimization presented is investigated in conjunction with research in Markov decision process.
The published articles aim to foster the development of research in Artificial intelligence, Machine learning, Mathematical optimization, Theoretical computer science and Natural language processing. The most cited papers explore research in Artificial intelligence alongside concepts in Domain (software engineering) and other areas of study in Structure (mathematical logic). The most cited papers focus on Machine learning but the discussions also offer insight into other areas such as Training set, Pattern recognition and Data mining.
Journal of Artificial Intelligence Research is organized to address concerns in the fields of Artificial intelligence, Theoretical computer science, Machine learning, Multi-agent system and Heuristics. Artificial intelligence research is concerned with Artificial neural network in particular. It dives deep in exploring the relationship between the study of Theoretical computer science and Computational complexity theory.
The research on Multi-agent system featured in it combines topics in other fields like Distributed computing, Markov decision process, Resource (project management) and Game theory. It features research on Heuristics in an attempt to reinforce studies in the field of Mathematical optimization. The study on Key (cryptography) presented in Journal of Artificial Intelligence Research intersects with the topics under Algorithm.
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 Journal of Artificial Intelligence Research (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 Journal of Artificial Intelligence Research (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, 90.70% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 12.50% 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 12.50% of all publications and 75.00% 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.
Embarking on a career in artificial intelligence research requires not only a keen interest in the field but also a solid educational background - often at the postgraduate level. Similar to fields such as data science and machine learning, aspiring AI researchers typically need to build strength in areas such as statistics and programming, as well as developing familiarity with the tools and technologies commonly used in AI. Aside from hard technical skills, creativity and critical thinking skills are also highly prized in this field, as AI researchers often need to design and implement novel solutions to complex problems. For those who gravitate towards teaching, a career in academia focusing on Artificial Intelligence research could be exciting. In fact, many of our journal contributors are educators who not only teach the next generation of AI professionals but also conduct groundbreaking research. Blending a passion for teaching and AI could potentially be a rewarding career choice. To make this transition simpler, we recommend that you familiarize yourself with the different roles in this field and their specific educational requirements. If you decide to follow this path, understanding the preschool teacher education requirements in Tennessee, for instance, can be a good starting point. Regardless of the path you choose, continuous learning and staying up to date with the latest AI news and research are a must for anyone seeking to break into and succeed in the field of artificial intelligence research. So, get started on your journey today by exploring the extent of AI research being done worldwide and finding your place in this exciting field.
Lu Cheng;Kush R. Varshney;Huan Liu
(2021)Unknown
(2021)Unknown
(2021)Unknown
(2023)Unknown
(2020)Shushman Choudhury;Kiril Solovey;Mykel J. Kochenderfer;Marco Pavone
(2021)Songül Tolan;Annarosa Pesole;Fernando Martínez-Plumed;Enrique Fernández-Macías
(2021)Samuel Läubli;Sheila Castilho;Graham Neubig;Rico Sennrich
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