| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 298 | 215 | 272 | 19 |
Algorithms mainly deals with areas of study such as Algorithm, Artificial intelligence, Mathematical optimization, Pattern recognition and Machine learning. The journal holds forums on Algorithm that merges themes from other disciplines such as Convergence (routing) and Set (abstract data type). The journal focuses on Artificial intelligence research which is adjacent to topics in Computer vision.
The research on Mathematical optimization discussed in Algorithms draws on the closely related field of Job shop scheduling.
The most cited papers mainly tackle studies in Algorithm, Artificial intelligence, Mathematical optimization, Machine learning and Fuzzy logic. The published papers hold forums on Algorithm that merge themes from other disciplines such as Data mining, Identification (information), Theoretical computer science and Benchmark (computing). The journal articles address concerns in Artificial intelligence which are intertwined with other disciplines, such as Computer vision and Pattern recognition.
The main points discussed in the journal deals with Artificial intelligence, Algorithm, Mathematical optimization, Set (abstract data type) and Deep learning. The studies on Artificial intelligence discussed can also contribute to research in the domains of Field (computer science), Machine learning and Pattern recognition. Most of the works presented in Algorithms deals with Algorithm but it intersects with the subject of Cluster analysis.
The Mathematical optimization study featured in the journal draws connections with the study of Benchmark (computing). The study on Set (abstract data type) presented is investigated in conjunction with research in Theoretical computer science.
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 Algorithms (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 Algorithms (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, 96.59% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 10.00% 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 0.00% 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.
While the journal highlights critical advancements in algorithmic learning and research, many readers following this field may also be interested in career possibilities and professional growth opportunities. One area worth exploring in this context is the teaching profession. A career in education could be particularly fulfilling as it allows you to contribute to shaping future generations of researchers and professionals in this field. If you're interested in a career in academia, you may want to consider pursuing a Master's degree. In the state of Maryland, specific requirements are set for those aspiring to become teachers. Moreover, your master's degree can specialize in areas such as algorithms, data science, artificial intelligence, or related fields, aligning with the themes discussed in this journal. Further details about the prerequisites, qualifications, certifications, and the application process to become a teacher can be found in this guide on how to become a teacher in Maryland with a master's degree. By gaining the necessary knowledge and formal qualifications, you can contribute to nurturing the next generation of professionals driving advancements in algorithms and related fields. Those who are looking to carve their path in this exciting field of study can find additional resources and potential opportunities on our website. Continued engagement with advancements in this field, like the ones discussed in our journal, will be instrumental in staying ahead within this evolving academic landscape.
Patrick Mikalef;John Krogstie;Ilias O. Pappas;Ilias O. Pappas;Paul A. Pavlou
(2020)Nebojsa Bacanin;Timea Bezdan;Eva Tuba;Ivana Strumberger
(2020)Unknown
(2022)Laith Abualigah;Amir H. Gandomi;Mohamed Abd Elaziz;Abdelazim G. Hussien
(2020)Stamatis Karlos;Georgios Kostopoulos;Sotiris Kotsiantis
(2020)Fevrier Valdez;Oscar Castillo;Patricia Melin
(2021)Athanasios Kallipolitis;Kyriakos Revelos;Ilias Maglogiannis
(2021)Exploring related online degrees can open diverse career opportunities in the ever-evolving tech industry. For those interested in expanding their technical skills with flexibility, an engineer degree online offers affordable pathways to careers in software, systems, and hardware engineering.
Creative minds can consider pursuing a degree in game design. Programs listed under the game development degree category prepare students for dynamic roles in gaming, animation, and interactive media—fields that demand both artistic and technical expertise.
As cybersecurity threats increase, earning an accredited online cyber security degree is crucial for building a career in protecting data and infrastructure. These programs emphasize real-world skills and industry certifications vital for security professionals.
For those passionate about data analytics, pursuing the best online data science masters can lead to roles in machine learning, AI, and business intelligence. These programs offer advanced training to harness big data for impactful decision-making.
