Expert Systems with Applications

Top Research Topics at Expert Systems With Applications?

Expert Systems With Applications facilitates discussions on Artificial intelligence, Data mining, Machine learning, Pattern recognition and Mathematical optimization. The study on Artificial intelligence presented in it intersects with subjects under the field of Computer vision. It explores issues in Data mining which can be linked to other research areas like Set (abstract data type) and Cluster analysis.

The Machine learning study featured in the journal draws connections with the study of Expert system. It connects the study in Expert system with the closely related area of Knowledge management. The Pattern recognition study tackled is a key component of adjacent topics in the area of Feature (computer vision).

The Mathematical optimization study featured in Expert Systems With Applications draws parallels with the field of Algorithm. The journal connects research in Fuzzy logic with the related topic of Operations research. The work on Fuzzy set operations tackled in it brings together disciplines like Defuzzification and Fuzzy classification.

• Artificial intelligence (38.77%)
• Data mining (18.66%)
• Machine learning (18.31%)

What are the most cited papers published in the journal?

• A GA-based feature selection and parameters optimizationfor support vector machines (1103 citations)
• A simple and fast algorithm for K-medoids clustering (1049 citations)
• Review: A state-of the-art survey of TOPSIS applications (980 citations)

Research areas of the most cited articles at Expert Systems With Applications:

The published papers focus largely on the fields of Artificial intelligence, Data mining, Machine learning, Artificial neural network and Fuzzy logic. The study of Artificial intelligence in the journal publications encompasses disciplines such as Pattern recognition, as well as fields such as Speech recognition, all of which overlap with one another. The journal papers focus on Fuzzy logic but the discussions also offer insight into other areas such as Mathematical optimization and Operations research.

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Statistics
• Law

The previous edition focused in particular on these issues:

The journal investigates areas of study like Artificial intelligence, Pattern recognition, Deep learning, Machine learning and Algorithm. Convolutional neural network, Artificial neural network, Feature (computer vision), Robustness (computer science) and Feature selection are all areas of Artificial intelligence tackled in the journal. While Artificial neural network is the focus of it, it also provided insights into the studies of Contextual image classification and Feature extraction.

The journal links adjacent topics like Pattern recognition with Transfer of learning. The research on Machine learning tackled can also make contributions to studies in the areas of Process (engineering) and Benchmark (computing). Many of the studies tackled connect Algorithm with a similar field of study like Fuzzy logic.

The most cited articles from the last journal are:

• Genetic Neural Architecture Search for automatic assessment of human sperm images (5 citations)
• Predicting Clinical Scores for Alzheimer’s Disease Based on Joint and Deep Learning (2 citations)
• Improving the state-of-the-art in the Traveling Salesman Problem: An Anytime Automatic Algorithm Selection (1 citations)

Papers citation over time

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.

Top authors and change over time

The top authors publishing in Expert Systems With Applications (based on the number of publications) are:

• Shyi-Ming Chen (54 papers) absent at the last edition,
• Tzung-Pei Hong (45 papers) absent at the last edition,
• So Young Sohn (43 papers) absent at the last edition,
• Loris Nanni (39 papers) absent at the last edition,
• Witold Pedrycz (37 papers) published 1 paper at the last edition, 1 less than at the previous edition.

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.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Expert Systems With Applications (based on the number of publications) are:

• National Cheng Kung University (223 papers) absent at the last edition,
• Hong Kong Polytechnic University (206 papers) published 1 paper at the last edition, 10 less than at the previous edition,
• National Taiwan University of Science and Technology (199 papers) absent at the last edition,
• National Chiao Tung University (185 papers) absent at the last edition,
• Yonsei University (173 papers) published 1 paper at the last edition, 20 less than at the previous edition.

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.

Publication chance based on affiliation

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, 16.79% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 3.67% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.50% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 11.01% of all publications and 79.82% were from other institutions.

Returning Authors Index

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.

Returning Institution Index

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.

The experience to innovation index

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:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career prospects and opportunities in Expert Systems and Applications

In the evolving field of Expert Systems and Applications, career prospects are plentiful and varied. Many of these roles blend computer vision, AI, and machine learning, essential subjects introduced in this article, into a rewarding and engaging career. Specifically, many professionals drawn to academia find great fulfillment in teaching positions that allow them to explore these areas of interest and impart their knowledge to the next generation.

For those with a passion for education, there are affordable ways to obtain the necessary qualifications to enter the field. One such option is through various teaching credential programs in Tennessee. These programs allow individuals with real-world experience in Expert Systems and AI to transition into an academic career.

Besides teaching, other career paths open to professionals in Expert Systems and Applications include positions like data scientist, machine learning engineer, AI specialist, and business intelligence developer, among others. As the field continues to evolve, it presents bountiful opportunities to apply skills in a variety of contexts and industries, making it a rewarding career choice for many.