| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 397 | 45 | 60 | 15 |
The journal mainly tackles studies in Artificial intelligence, World Wide Web, Machine learning, Pattern recognition and Human–computer interaction. Topics in Artificial intelligence were tackled in line with various other fields like Computer vision and Natural language processing. It focuses on World Wide Web as well as the interrelated topic of Multimedia.
The journal papers cover a variety of subjects, including Artificial intelligence, Machine learning, World Wide Web, Analytics and Computer vision. While the published papers focused on Artificial intelligence, they were also able to explore topics like Turing and Dream. The journal articles hold forums on World Wide Web that merge themes from other disciplines such as Surprise, Metaverse and Measure (data warehouse).
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 Interactive Multimedia and Artificial Intelligence (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 Interactive Multimedia and Artificial Intelligence (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, 97.30% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 100.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 0.00% 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 0.00% 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.
We have also discovered that the interdisciplinary nature of Interactive Multimedia and Artificial Intelligence opens up a wide range of career opportunities in various sectors. For instance, professionals in this field may work as data analysts, software developers, computer systems analysts, or information security analysts. In addition to these, individuals can also explore niche roles such as high school history teachers with a focus on technologically-enhanced interactive teaching via multimedia and AI tools. To gain a concrete understanding of one of these unique career paths, let us consider the role of a high school history teacher in Arizona. This role often requires the individual to incorporate multimedia and AI tools to enhance student understanding of complex historical events and periods. Teachers need to ensure their learning materials are not only informative but also interactively engaging. For more insights on how to embark on such a career, visit how to become a high school history teacher in Arizona. This resource provides a comprehensive guide on the educational requirements, necessary certifications, and detailed job descriptions of a history teacher with a specialty in using advanced interactive multimedia tools. The guide also sheds light on various ways to effectively use AI tools to foster an engaging and interactive learning environment. As the field of Artificial Intelligence continues to evolve, there's no doubt that many more unique job roles will emerge in the near future.
Simon James Fong;Gloria Li;Nilanjan Dey;Rubén Gonzalez-Crespo
(2020)Simon James Fong;Gloria Li;Nilanjan Dey;Rubén González Crespo
(2020)Sumit Kumar;Vijender Kumar-Solanki;Saket Kumar Choudhary;Ali Selamat
(2020)Alicia García-Holgado;Samuel Marcos-Pablos;Francisco García-Peñalvo
(2020)José Carlos Sánchez-Prieto;Juan Cruz-Benito;Roberto Therón;Francisco García-Peñalvo
(2020)Sitara Afzal;Muazzam Maqsood;Umair Khan;Irfan Mehmood
(2021)Salah Kamel;Francisco Jurado;Hamdy M. Sultan;Ahmed S. Menesy
(2020)Exploring Computer Science education in the USA often leads students to consider various degree formats and timelines. For those looking to accelerate their learning, there are online PhD programs that offer flexible scheduling without compromising academic rigor.
If you prefer a more condensed route, 1 year masters program options are increasingly popular. These programs deliver focused curricula, helping students quickly gain advanced knowledge and specialize in high-demand areas like artificial intelligence or data science.
For those balancing career changes or upskilling, considering some of the easiest online degrees that pay well can be a smart strategy. Such degrees blend practicality with time efficiency and strong earning potential.
Lastly, it’s crucial to align your studies with future job market trends. Reviewing the best majors for the future can help you make informed decisions about career pathways that promise growth and sustainability in the tech industry.
