Thirty years of the international journal of intelligent systems: a bibliometric review

The International Journal of Intelligent Systems was created in 1986. Today, the journal is 30 years old. To celebrate this anniversary, this study develops a bibliometric review of all of the papers published in the journal between 1986 and 2015. The results are largely based on the Web of Science Core Collection, which classifies leading bibliographic material by using several indicators including total number of publications and citations, the h-index, cites per paper, and citing articles. Thework also uses theVOS viewer software for visualizing the main results through bibliographic coupling and co-citation. The results show a general overview of leading trends that have influenced the journal in terms of highly cited papers, authors, journals, universities and countries. C 2016 Wiley Periodicals, Inc

A webometric analysis of Australian Universities using staff and size dependent web impact factors (WIF)

This study describes how search engines (SE) can be employed for automated, efficient data gathering for Webometric studies using predictable URLs. It then compares the usage of staffrelated Web Impact Factors (WIFs) to sizerelated impact factors for a ranking of Australian universities, showing that rankings based on staffrelated WIFs correlate much better with an established ranking from the Melbourne Institute than commonly used sizedependent WIFs. In fact sizedependent WIFs do not correlate with the Melbourne ranking at all. It also compares WIF data for Australian Universities provided by Smith (1999) for a longitudinal comparison of the WIF of Australian Universities over the last decade. It shows that sizedependent WIF values declined for most Australian universities over the last ten years, while staffdependent WIFs rose

A fuzzy-based scoring rule for author ranking

The measurement of the quality of research has reached nowadays an increasing interest not only for scientific reasons but also for the critical problem of researchers' ranking, due to the lack of grant assignments. The most commonly used approach is based on the so-called $h$-index, even if the current literature debated a lot about its pros and cons. This paper, after a brief review of the $h$-index and of alternative models, focuses on the characterization and the implementation of a modified scoring rule approach by means of a fuzzy inference system a là Sugeno.Research evaluation, bibliometrics, author ranking, $h$-index, scoring rules, fuzzy inference system.

The Research Space: using the career paths of scholars to predict the evolution of the research output of individuals, institutions, and nations

In recent years scholars have built maps of science by connecting the academic fields that cite each other, are cited together, or that cite a similar literature. But since scholars cannot always publish in the fields they cite, or that cite them, these science maps are only rough proxies for the potential of a scholar, organization, or country, to enter a new academic field. Here we use a large dataset of scholarly publications disambiguated at the individual level to create a map of science-or research space-where links connect pairs of fields based on the probability that an individual has published in both of them. We find that the research space is a significantly more accurate predictor of the fields that individuals and organizations will enter in the future than citation based science maps. At the country level, however, the research space and citations based science maps are equally accurate. These findings show that data on career trajectories-the set of fields that individuals have previously published in-provide more accurate predictors of future research output for more focalized units-such as individuals or organizations-than citation based science maps

OWA operators in the calculation of the average green-house gases emissions

This study proposes, through weighted averages and ordered weighted averaging operators, a new aggregation system for the investigation of average gases emissions. We present the ordered weighted averaging operators gases emissions, the induced ordered weighted averaging operators gases emissions, the weighted ordered weighted averaging operators gases emissions and the induced probabilistic weighted ordered weighted averaging operators gases emissions. These operators represent a new way of analyzing the average gases emissions of different variables like countries or regions. The work presents further generalizations by using generalized and quasi-arithmetic means. The article also presents an illustrative example with respect to the calculations of the average gases emissions in the European region

Aggregation operators in group decision making: Identifying citation classics via H-classics

To analyze the past, present and future of a particular research field, classic papers are usually studied because they identify the highly cited papers being a relevant reference point in that specific research area. As a result of the possible mapping between high quality research and high citation counts, highly cited papers are very interesting. The objective of this study is to use the H-classics method, which is based on the popular h-index, to identify and analyze the highly cited documents published about aggregation operators in the research area of group decision making. According to the H-classics method, this research area is represented by 87 citation classics, which have been published from 1988 to 2014. Authors, affiliations (universities/institutions and countries), journals, books and conferences, and the topics covered by these 87 highly cited papers are studied.The authors would like to thank FEDER financial support from the Projects TIN2013-40658-P and TIN2016- 75850-P