| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 1125 | 6 | 9 | 1 |
International Journal of Data Mining, Modelling and Management was organized to reinforce research efforts on Data mining, Artificial intelligence, Machine learning, Cluster analysis and Pattern recognition. It holds forums on Data mining that merges themes from other disciplines such as Genetic algorithm and Set (abstract data type). The study on Artificial intelligence presented in the journal intersects with subjects under the field of Natural language processing.
The study on Machine learning featured in International Journal of Data Mining, Modelling and Management expounds on the topic of Decision tree in particular. The journal primarily discusses Cluster analysis topics, particularly Correlation clustering, CURE data clustering algorithm, Fuzzy clustering, k-means clustering and Hierarchical clustering. The works on Correlation clustering deal in particular with Canopy clustering algorithm.
The journal encompasses presentations on CURE data clustering algorithm, specifically Data stream clustering and Single-linkage clustering. Feature vector is a primary topic of Pattern recognition research in it. It emphasizes research on Support vector machine, which includes concerns such as Naive Bayes classifier.
The most cited papers investigate areas of study like Data mining, Artificial intelligence, Machine learning, Text mining and Classifier (UML). The journal papers facilitate discussions on Data mining that incorporate concepts from other fields like Raw data and Data collection. The studies on Machine learning discussed at the most cited publications can also contribute to research in the domains of Binary decomposition and Pattern recognition.
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 International Journal of Data Mining, Modelling and Management (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 International Journal of Data Mining, Modelling and Management (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, 100.00% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, nan% were posted by at least one author from the top 10 institutions publishing in the journal. Another nan% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included nan% of all publications and nan% 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.
If you are a researcher or a scholar interested in contributing to the International Journal of Data Mining, Modelling and Management, it is crucial to understand the submission requirements and review process. The journal encourages high-quality, well-researched papers across a breadth of topics in the data mining, modelling and management field. Before submitting, authors should carefully review the suitability of their manuscript for the journal, the novelty and practical implication of their research, and the clarity of the presentation. The manuscript submitted should be formatted as per the journal's submission guidelines and should not have been published or under review elsewhere. In addition to conventional research papers, the journal also welcomes review papers, short communications, and reports from conferences and workshops. University-affiliated researchers, especially those pursuing a career in fields like teaching or assistance, often contribute to these types of publications. For those interested in education-related careers, it could be beneficial to understand the prerequisites such as the [teacher assistant certificate requirements in Maryland](https://research.com/careers/how-to-become-a-preschool-teacher-assistant-in-maryland). This could provide an additional advantage to researchers planning to pursue roles in academia. The International Journal of Data Mining, Modelling and Management follows a double-blind peer review process which ensures both the reviewers and the authors remain anonymous during the process. The reviewers are selected based on their expertise in the relevant field. Authors should strive to provide insightful and novel contributions to the field and clearly articulate their research findings. It’s important to realize that the process from submission to publication can be quite lengthy and can often take up to several months. Nevertheless, contributing to such a widely recognized and respected journal could significantly enhance a researcher's academic profile and open up further academic and career opportunities.
Akram Osman;Naomie Salim
(2020)Hiba Zuhair;Ali Selamat
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