Finding the most suitable co-author is one of the most important ways to conduct effective research in scientific fields. Data science has contributed to achieving this possibility significantly. The present study aims at designing a mathematical model of co-author recommender system in...

Identifying investment patterns as part of customer segmentation is one of the most important tasks in retail banking. Clustering customers efectively is an important element of improving marketing policy and strategic planning. There are several methods for identifying similar groups of...

The study aimed to present an integrated model for evaluation of big data (BD) challenges and analytical methods in recommender systems (RSs). The proposed model used fuzzy multi-criteria decision making (MCDM) which is a human judgment-based method for weighting of RSs’ properties. Human...

The study aimed to propose a judgment-based evaluation model for usability evaluating of interactive systems. Human judgment is associated with uncertainty and gray information. We used the fuzzy technique for integration, summarization, and distance calculation of quality value judgment. The...

The data presented in this article are related to the published article entitled “A Judgment-Based Model for Usability Evaluating of Interactive Systems Using Fuzzy Multi Factors Evaluation (MFE)” in “Applied Soft Computing” [1]. The purpose of data collection in this paper was to...

The purpose of this study was to analyze the competitive situation of the cheminformatics industry using Porter’s competitive model and to determine the priority and weight of each competitive force in this industry. In addition to qualitative analysis of data collected from library surveys...

With the increasing development of information and scientific databases, scientific collaboration has expanded in health sciences. This study aims to prioritize the criteria that affect finding potential author matches in bioinformatics using fuzzy Multiple Criteria Decision Making (MCDM)...

Investment decisions are influenced by various factors, including personal characteristics and managerial issues. In this research, we aimed to investigate the impact of managerial traits on investment decisions by using adaptive neuro-fuzzy inference system (ANFIS) to develop a personalized...

The proposed model is an adaptive neuro-fuzzy inference recommender system that utilizes customer investment service feedback and fuzzy neural inference solutions to generate personalized investment recommendations. The model is designed to support the investment process for the customers and...

This article presents an investment recommender system based on an Adaptive NeuroFuzzy Inference System (ANFIS) and pre-trained weights from a Multimodal Neural Network (MNN). The model is designed to support the investment process for the customers and takes into consideration seven factors to...