| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 286 | 15 | 30 | 10 |
| Computer Science | 509 | 64 | 77 | 11 |
Annals of Mathematics and Artificial Intelligence is organized to address concerns in the fields of Complex system, Artificial intelligence, Theoretical computer science, Discrete mathematics and Algorithm. Complex system research featured in the journal incorporates concerns from various other topics such as Artificial neural network, Computation and Mathematical optimization. It addresses concerns in Artificial intelligence which are intertwined with other disciplines, such as Machine learning, Pattern recognition and Natural language processing.
The work on Theoretical computer science tackled in the journal brings together disciplines like Programming language, Set (abstract data type) and Inference. While it focused on Discrete mathematics, it was also able to explore topics like Class (set theory), Combinatorics and Algebra.
The most cited papers generally zeroe in on subjects such as Complex system, Artificial intelligence, Theoretical computer science, Discrete mathematics and Algorithm. While Complex system is the key highlight in the journal papers, thet also covered some subjects on Mathematical optimization and Set (abstract data type). The journal publications explore topics in Artificial intelligence which can be helpful for research in disciplines like Deontic logic and Machine learning.
The journal explores disciplines such as Complex system, Algorithm, Theoretical computer science, Artificial intelligence and Set (abstract data type). Complex system research presented in the journal encompasses a variety of subjects, including Belief revision, Non-monotonic logic, Probabilistic logic, Relation (database) and Optimization problem. The research on Algorithm tackled can also make contributions to studies in the areas of Domain (software engineering), Density estimation, Cluster analysis, Constraint (information theory) and Subgradient method.
The research on Theoretical computer science featured in Annals of Mathematics and Artificial Intelligence combines topics in other fields like Directed graph, Relational database, Heuristic and Orders of magnitude (bit rate). In the journal, Machine learning, Clique and Combinatorial testing are investigated in conjunction with one another to address concerns in Artificial intelligence research. The studies on Set (abstract data type) discussed can also contribute to research in the domains of Interpretation (logic), Terminology, Boolean function, Finite set and Certificate.
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 Annals of Mathematics and 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 Annals of Mathematics and 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 2021 edition, 13.04% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 13.33% were posted by at least one author from the top 10 institutions publishing in the journal. Another 6.67% 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 70.00% 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.
Vitaly Kuznetsov;Mehryar Mohri
(2020)Shaowen Lan;Shaowen Lan;Wenjuan Fan;Wenjuan Fan;Shanlin Yang;Shanlin Yang;Panos M. Pardalos
(2021)Abtin Nourmohammadzadeh;Stefan Voß
(2021)Kayla Jacobs;Alon Itai;Shuly Wintner
(2020)Hananel Hazan;Daniel J. Saunders;Darpan T. Sanghavi;Hava T. Siegelmann
(2020)Min Kong;Min Kong;Xinbao Liu;Xinbao Liu;Jun Pei;Jun Pei;Jun Pei;Hao Cheng;Hao Cheng
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French Institute for Research in Computer Science and Automation - INRIA
Publications: 2
