Purpose This study reviews the methods found in the literature for the ranking of authors,
identifies the pros and cons of these methods, discusses and compares these methods. The …

Deep Neural Network (DNN) testing is one of the most widely-used ways to guarantee the
quality of DNNs. However, labeling test inputs to check the correctness of DNN prediction is …

People have looked for experts since before the advent of computers. With advances in
information retrieval technology and the large-scale availability of digital traces of …

Young scholars in academia often seek to work in collaboration with top researchers in their
field in pursuit of a successful career. While success in academia can be defined differently …

Expert finding is an information retrieval task that is concerned with the search for the most
knowledgeable people with respect to a specific topic, and the search is based on …

Advisor–advisee relationship is important in academic networks due to its universality and
necessity. Despite the increasing desire to analyze the career of newcomers, however, the …

Expert finding is an information retrieval task concerned with the search for the most
knowledgeable people, in some topic, with basis on documents describing peoples …

The total number of published articles and the resulting citations are generally
acknowledged as suitable criteria of the scientist's evaluation. However, it is challenging to …

Expert finding problem in bibliographic networks has received increased interest in recent
years. This problem concerns finding relevant researchers for a given topic. Motivated by the …

Local experts are critical for many location-sensitive information needs, and yet there is a
research gap in our understanding of the factors impacting who is recognized as a local …