| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Computer Science | 451 | 53 | 59 | 13 |
Applied Artificial Intelligence mainly tackles studies in Artificial intelligence, Machine learning, Data mining, Artificial neural network and Pattern recognition. Expert system is a major topic of Artificial intelligence research.
The journal papers explore disciplines such as Artificial intelligence, Machine learning, Human–computer interaction, Domain (software engineering) and Data mining. The majority of Artificial intelligence studies in the journal publications are focused on the issues of Artificial neural network. Issues in Human–computer interaction were discussed in the published papers, taking into consideration concepts from other disciplines like Context (language use) and Multimedia.
Applied Artificial Intelligence was organized to reinforce research efforts on Artificial intelligence, Machine learning, Deep learning, Pattern recognition and Artificial neural network. Artificial intelligence research featured in Applied Artificial Intelligence incorporates concerns from various other topics such as Computer vision and Natural language processing. It links adjacent topics like Machine learning with Classifier (UML).
It facilitated discussions that integrated Deep learning and Agricultural engineering. The journal focused on Pattern recognition research but expanded to cover Set (abstract data type). Applied Artificial Intelligence held discussions to help close the divide between two different fields of study: Artificial neural network and League.
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 Applied 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 Applied 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, 14.63% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 5.71% 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 11.43% of all publications and 82.86% 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.
While the research of Applied Artificial Intelligence focuses mainly on aspects like artificial intelligence, machine learning, and data mining, it's worth exploring its potential applications in various fields, such as education. For instance, the process of teaching and learning can be significantly enhanced by implementing AI-powered solutions.
Artificial Intelligence can support personalized learning by adapting educational content according to individual student's needs and pace. Machine learning algorithms can analyze each student's capabilities, progress, and learning style, and suggest customized learning plans for every student.
Moreover, educators can apply data mining techniques to discover meaningful patterns and correlations in tons of educational data, enabling them to make more informed and effective teaching decisions. For example, teachers can identify the teaching methods that work best for certain groups of students based on the patterns uncovered.
A particular area where AI has a significant influence is in enhancing the role of an elementary school teacher requirements Delaware. AI can automate administrative tasks, allowing teachers to spend more time interacting with students and improving the learning experience.
Overall, incorporating Applied Artificial Intelligence in the field of education can create productive and meaningful learning experiences while alleviating teachers' workload.
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(2021)Emmanuel Okewu;Phillip Adewole;Sanjay Misra;Rytis Maskeliunas
(2021)Unknown
(2022)Tianhua Chen;Grigoris Antoniou;Marios Adamou;Ilias Tachmazidis
(2021)Vithya Yogarajan;Bernhard Pfahringer;Michael Mayo
(2020)For students pursuing Computer Science in the USA, exploring online degrees can offer flexible and accessible pathways to enhance skills and advance careers. Choosing a self paced university allows learners to balance studies with work or personal commitments, making education more manageable and tailored to individual needs.
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