| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 281 | 45 | 68 | 21 |
| Business and Management | 476 | 9 | 12 | 6 |
| Engineering and Technology | 879 | 22 | 27 | 9 |
The journal primarily tackles Artificial intelligence, Data mining, Mathematical optimization, Operations research and Knowledge management. Issues in Artificial intelligence were discussed, taking into consideration concepts from other disciplines like Machine learning and Pattern recognition. The work on Data mining addressed in the journal expands to the thematically related Cluster analysis.
The research on Mathematical optimization featured in International Journal of Information Technology and Decision Making combines topics in other fields like Set (abstract data type) and Fuzzy logic. Topics like Fuzzy set and Fuzzy number are tackled as part of the discussions on Fuzzy logic. The journal explores research in Fuzzy number and the adjacent study of Fuzzy set operations.
It tackles issues in Operations research, particularly in the topics of Analytic hierarchy process and Multiple-criteria decision analysis. Research on Multiple-criteria decision analysis addressed in the journal frequently intersections with the field of TOPSIS.
The journal publications primarily focus on research topics in Data mining, Artificial intelligence, Mathematical optimization, Fuzzy logic and Analytic hierarchy process. The published articles facilitate discussions on Data mining that incorporate concepts from other fields like Value (computer science), Field (computer science) and Data science. While the most cited publications focused on Artificial intelligence, they were also able to explore topics like Machine learning, Preference, Decision analysis and Pattern recognition.
The foci of International Journal of Information Technology and Decision Making are Artificial intelligence, Risk analysis (engineering), Analytic hierarchy process, Data mining and Operations research. Artificial intelligence research featured in the journal incorporates concerns from various other topics such as Machine learning and Pattern recognition. International Journal of Information Technology and Decision Making addresses concerns in Risk analysis (engineering) which are intertwined with other disciplines, such as Domain (software engineering) and Risk assessment.
Analytic hierarchy process research presented in International Journal of Information Technology and Decision Making encompasses a variety of subjects, including Context (language use), Management science, Industrial engineering, TOPSIS and Ranking. The study on Data mining presented is investigated in conjunction with research in Cluster analysis. The works on Operations research deal in particular with Multiple-criteria decision analysis.
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 Information Technology and Decision Making (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 Information Technology and Decision Making (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, 11.39% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 20.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 14.29% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 12.86% of all publications and 52.86% 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.
Understanding the application of these research areas in real-world careers can be insightful for both current students and professionals looking to focus their studies or career paths. For instance, knowledge in Artificial Intelligence, Data Mining, and Mathematical Optimization can be incredibly useful in careers such as Urban Planning. Becoming an Urban Planner involves applying scientific analysis, creative design, and sociopolitical concepts to develop and implement plans for the use of land in cities. This can include aspects of transportation systems, parks and recreational facilities, residential areas, and commercial development. For example, an Urban Planner might use AI and Data Mining to analyze patterns and trends in housing data, transportation usage, public opinion surveys, and demographic information. This information can then be used to predict future needs and growth patterns, allowing for more effective and sustainable urban development. In Massachusetts, aspiring Urban Planners can study at some of the state's highly regarded universities, which offer various programs integrating these fundamental areas of study. If you're considering a career in Urban Planning, you might find it beneficial to view the list of top business schools in Massachusetts which can provide a robust foundation in these areas. In essence, the practical application of the research published in the International Journal of Information Technology and Decision Making extends far beyond the academic arena, providing essential knowledge and skills for diverse professionals, innovators, and thought leaders in the ever-evolving technological landscape.
Dejian Yu;Gang Kou;Zeshui Xu;Shunshun Shi
(2021)R. T. Mohammed;A. A. Zaidan;R. Yaakob;N. M. Sharef
(2021)Fuji Ren;Fuji Ren;Yanwei Bao
(2020)Unknown
(2021)Jafar Rezaei
(2020)Ahmed Shihab Albahri;Jameel R. Al-Obaidi;A. A. Zaidan;Osamah Shihab Albahri
(2020)Karrar Hameed Abdulkareem;Karrar Hameed Abdulkareem;Nureize Arbaiy;A. A. Zaidan;B. B. Zaidan
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