Abstract Introduction Bibliometrics enable the objective assessment of a journals quality and prestige, making them vital to academic surgical integrity. This paper systematically reviews evidence for current journal-ranking platforms. Method An initial systematic search identified published journal bibliometrics on 5th November 2019. Studies assessing were through second OVID Medline database ...

In this paper, we identify a novel and interesting type of queries, contextual ranking queries, which return the ranks of query tuples among some context tuples given in the queries. Contextual ranking queries are useful for olap and decision support applications in non-traditional data exploration. They provide a mechanism to quickly identify where tuples stand within the context. In this pape...

The notion of Intuitionistic Fuzzy Numbers (IFNs) has been improved in many decision making problems. Ranking of IFNs is one of the techniques that conceptualize IFNs to illustrate order or preference in decision making. Ranking of IFNs plays a very important role in multicriteria decision making, optimization and in many different fields but ranking of IFNs is not a very easy process. As far a...

In this paper we propose to use nonparametric scoring methods based on ranking trees as a support decision tool for medical diagnosis. The proposed algorithms enable to order cohorts of patients according to the risk level of developing a particular disease. The aim of this paper is to illustrate the potential of various algorithms using ranking trees, particularly the variants with bagging-typ...

Ranking search results is an ongoing research topic in information retrieval. The traditional models are the vector space, probabilistic and language models, and more recently machine learning has been deployed in an effort to learn how to rank search results. Categorization of search results has also been studied as a means to organize the results, and hence to improve users search experience....

Machine learning ranking methods are increasingly applied to ranking tasks in information retrieval (IR). However ranking tasks in IR often differ from standard ranking tasks in machine learning, both in terms of problem structure and in terms of the evaluation criteria used to measure performance. Consequently, there has been much interest in recent years in developing ranking algorithms that ...

In this paper attention has been paid to the study of a new ranking procedure for trapezoidal intuitionistic fuzzy number (TRIFN). There are numerous methods for ranking of simple fuzzy numbers but, we lack of effective methods for ranking of intuitionistic fuzzy numbers (IFN). To serve the purpose, the value and ambiguity index of TRIFNs have been defined. In order to rank TRIFNs, we have defi...