| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 323 | 68 | 92 | 18 |
The main research concerns discussed in Journal of Intelligent Information Systems are Artificial intelligence, Data mining, Information retrieval, Machine learning and Data science. Artificial intelligence research featured in Journal of Intelligent Information Systems incorporates concerns from various other topics such as Pattern recognition, Recommender system, Task (project management) and Natural language processing. The Data mining study featured in it draws connections with the study of Cluster analysis.
Many of the studies tackled connect Information retrieval with a similar field of study like Set (abstract data type).
The journal articles are organized to reinforce research efforts on Artificial intelligence, Machine learning, Information retrieval, Database and Data mining. The published papers explore Artificial intelligence concepts, specifically Machine discovery but expand to research in Physical system. The most cited publications hold forums on Information retrieval that merge themes from other disciplines such as Deductive database and Natural language.
Journal of Intelligent Information Systems investigates areas of study like Artificial intelligence, Data science, Recommender system, Natural language processing and Machine learning. The studies on Artificial intelligence discussed can also contribute to research in the domains of Task (project management) and Pattern recognition. It explores research in Data science alongside concepts in Context (language use) and other areas of study in Topic model.
Recommender system research presented in the journal encompasses a variety of subjects, including Matrix decomposition, Feature (machine learning), Data mining and Missing data. The research on Natural language processing tackled can also make contributions to studies in the areas of Semantics, Word (computer architecture) and Identification (information). Most of the Machine learning studies addressed also intersect with Class (biology).
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 Journal of Intelligent Information 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 Journal of Intelligent Information 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, 30.86% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 17.86% were posted by at least one author from the top 10 institutions publishing in the journal. Another 21.43% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 10.71% of all publications and 50.00% 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.
After reading about all the research topics and revolutionary studies in the Journal of Intelligent Information Systems, one might be wondering about career possibilities in this field. Intelligent Information Systems is a broad field with burgeoning career opportunities. With the continuous evolution of technology and data-driven decision-making, careers in this field are rapidly expanding. You could be a Data scientist, Information systems manager, Business intelligence analyst, Systems engineer, and many other roles depending on your interests and skills. If you're interested in teaching, you could also consider becoming a history teacher with a deep understanding of intelligent information systems.
For those interested in both technological and historical studies, you might also want to look at our other articles on how to be a history teacher in New Jersey. Your unique combination of skills and knowledge in intelligent information systems will certainly be in high demand in the changing world of education.
Thi Ngoc Trang Tran;Alexander Felfernig;Christoph Trattner;Andreas Holzinger
(2021)Chun Yueh Chiu;Hsien Yuan Lane;Jia Ling Koh;Arbee L. P. Chen
(2021)Min Yen Wu;Chih-Ya Shen;En Tzu Wang;Arbee L. P. Chen
(2020)Nishant Jain;Abhinav Tomar;Prasanta K. Jana
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