| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 17 | 855 | 1611 | 91 |
Artificial intelligence, Data mining, Machine learning, Pattern recognition and Algorithm are among the topics commonly tackled in Knowledge Based Systems. The Artificial intelligence study featured in it draws parallels with the field of Natural language processing. Data mining research featured in the journal incorporates concerns from various other topics such as Data set, Set (abstract data type) and Fuzzy logic.
Knowledge Based Systems concentrates on Fuzzy logic topics that focus on Fuzzy set and Fuzzy number. The journal connects the study in Fuzzy number with the closely related area of Fuzzy set operations. The work on Fuzzy set operations addressed in Knowledge Based Systems expands to the thematically related Fuzzy classification.
It facilitates discussions on Machine learning that incorporate concepts from other fields like Classifier (UML) and Process (engineering). The work on Pattern recognition presented in Knowledge Based Systems focuses on Support vector machine in particular.
The main points discussed in the published papers deal with Artificial intelligence, Data mining, Machine learning, Pattern recognition and Fuzzy logic. The published articles explore research in Artificial intelligence and the adjacent study of Natural language processing. Issues in Data mining were discussed in the most cited articles, taking into consideration concepts from other disciplines like Recommender system, Data set, Set (abstract data type) and Cluster analysis.
The main research concerns discussed in Knowledge Based Systems are Artificial intelligence, Machine learning, Pattern recognition, Algorithm and Deep learning. Artificial intelligence research in Knowledge Based Systems involves the investigation of Natural language processing studies, all of which are linked to disciplines such as Word (computer architecture). Knowledge Based Systems explores topics in Machine learning which can be helpful for research in disciplines like Representation (mathematics), Task (project management) and Process (engineering).
Knowledge Based Systems holds forums on Pattern recognition that merges themes from other disciplines such as Image (mathematics) and Cluster analysis. Discussions in it are anchored in the subject of Cluster analysis and the similar topic of Data mining. The journal focused on Benchmark (computing) research but expanded to cover Optimization problem.
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 Knowledge Based Systems (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 Knowledge Based Systems (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, 5.59% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 19.49% were posted by at least one author from the top 10 institutions publishing in the journal. Another 10.32% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.14% of all publications and 51.04% 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.
One crucial aspect to consider in contributing to Knowledge Based Systems is having the proper educational background. This revolves around a deep understanding of artificial intelligence, data mining, machine learning, pattern recognition, and fuzzy logic. Those interested should consider obtaining a teaching credential in this field. In fact, Michigan offers some of the most cost-effective programs for obtaining a teaching credential.
One exceptional option can be found in our related article outlining the cheapest teaching credential program in Michigan. This could provide an excellent foundational understanding to contribute scholarly research to this ever-evolving field. By leveraging educational opportunities, interested individuals can substantially contribute to the current body of work, push boundaries of current understanding, and steer future research in Knowledge Based Systems.
Afshin Faramarzi;Mohammad Heidarinejad;Brent E. Stephens;Seyedali Mirjalili
(2020)Xin He;Kaiyong Zhao;Xiaowen Chu
(2021)Unknown
(2022)Funa Zhou;Funa Zhou;Shuai Yang;Hamido Fujita;Danmin Chen
(2020)Arwa Aldweesh;Abdelouahid Derhab;Ahmed Z. Emam
(2020)Bin Liang;Hang Su;Lin Gui;Erik Cambria
(2022)Saptarshi Sengupta;Sanchita Basak;Pallabi Saikia;Sayak Paul
(2020)Shenglei Chen;Geoffrey I. Webb;Linyuan Liu;Xin Ma
(2020)Pei Hu;Jeng-Shyang Pan;Shu-Chuan Chu;Shu-Chuan Chu
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