What attracts vehicle consumers’ buying:A Saaty scale-based VIKOR (SSC-VIKOR) approach from after-sales textual perspective?

Purpose: The increasingly booming e-commerce development has stimulated vehicle consumers to express individual reviews through online forum. The purpose of this paper is to probe into the vehicle consumer consumption behavior and make recommendations for potential consumers from textual comments viewpoint. Design/methodology/approach: A big data analytic-based approach is designed to discover vehicle consumer consumption behavior from online perspective. To reduce subjectivity of expert-based approaches, a parallel Naïve Bayes approach is designed to analyze the sentiment analysis, and the Saaty scale-based (SSC) scoring rule is employed to obtain specific sentimental value of attribute class, contributing to the multi-grade sentiment classification. To achieve the intelligent recommendation for potential vehicle customers, a novel SSC-VIKOR approach is developed to prioritize vehicle brand candidates from a big data analytical viewpoint. Findings: The big data analytics argue that “cost-effectiveness” characteristic is the most important factor that vehicle consumers care, and the data mining results enable automakers to better understand consumer consumption behavior. Research limitations/implications: The case study illustrates the effectiveness of the integrated method, contributing to much more precise operations management on marketing strategy, quality improvement and intelligent recommendation. Originality/value: Researches of consumer consumption behavior are usually based on survey-based methods, and mostly previous studies about comments analysis focus on binary analysis. The hybrid SSC-VIKOR approach is developed to fill the gap from the big data perspective

Cómputo con palabras para la evaluación de pares estudiantiles en presentaciones orales

La evaluación por pares en una presentación oral puede motivar y dar más sentido de responsabilidad a los estudiantes. En los últimos años, se han propuesto varios métodos para evaluar a los pares. En este artículo, se propone un método novedoso de evaluación en línea entre pares para la presentación oral utilizando la computación perceptiva. El resultado del sistema propuesto puede ser una puntuación numérica para la evaluación general de un estudiante en la presentación, que permite comparar y clasificar el desempeño del estudiante. además, del sistema se obtiene una evaluación lingüística que describe el desempeño del alumno. Se ha realizado un estudio de caso para mostrar la efectividad del método propuesto, luego se analizan y revisan los resultado

Cómputo con palabras para la evaluación de pares estudiantiles en presentaciones orales

Peer assessment in an oral presentation can motivate and give more sense of responsibility to students. In recent years, various methods have been proposed to evaluate peers. In this paper, a novel peer online assessment method is proposed for oral presentation using perceptual computing. The output of the proposed system can be a numerical score for the overall assessment of a student in the presentation, which allows comparison and ranking of student performance. Furthermore, a linguistic evaluation that describes the student's performance is obtained from the system. A case study has been conducted to show the effectiveness of the proposed method; then the results are analyzed and reviewed.La evaluación por pares en una presentación oral puede motivar y dar más sentido de responsabilidad a los estudiantes. En los últimos años, se han propuesto varios métodos para evaluar a los pares. En este artículo, se propone un método novedoso de evaluación en línea entre pares para la presentación oral utilizando la computación perceptiva. El resultado del sistema propuesto puede ser una puntuación numérica para la evaluación general de un estudiante en la presentación, que permite comparar y clasificar el desempeño del estudiante. además, del sistema se obtiene una evaluación lingüística que describe el desempeño del alumno. Se ha realizado un estudio de caso para mostrar la efectividad del método propuesto, luego se analizan y revisan los resultados

A Multi-criteria Decision Support System for Ph.D. Supervisor Selection: A Hybrid Approach

Selection of a suitable Ph.D. supervisor is a very important step in a student’s career. This paper presents a multi-criteria decision support system to assist students in making this choice. The system employs a hybrid method that first utilizes a fuzzy analytic hierarchy process to extract the relative importance of the identified criteria and sub-criteria to consider when selecting a supervisor. Then, it applies an information retrieval-based similarity algorithm (TF/IDF or Okapi BM25) to retrieve relevant candidate supervisor profiles based on the student’s research interest. The selected profiles are then re-ranked based on other relevant factors chosen by the user, such as publication record, research grant record, and collaboration record. The ranking method evaluates the potential supervisors objectively based on various metrics that are defined in terms of detailed domain-specific knowledge, making part of the decision making automatic. In contrast with other existing works, this system does not require the professor’s involvement and no subjective measures are employed

CBR and MBR techniques: review for an application in the emergencies domain

The purpose of this document is to provide an in-depth analysis of current reasoning engine practice and the integration strategies of Case Based Reasoning and Model Based Reasoning that will be used in the design and development of the RIMSAT system. RIMSAT (Remote Intelligent Management Support and Training) is a European Commission funded project designed to: a.. Provide an innovative, 'intelligent', knowledge based solution aimed at improving the quality of critical decisions b.. Enhance the competencies and responsiveness of individuals and organisations involved in highly complex, safety critical incidents - irrespective of their location. In other words, RIMSAT aims to design and implement a decision support system that using Case Base Reasoning as well as Model Base Reasoning technology is applied in the management of emergency situations. This document is part of a deliverable for RIMSAT project, and although it has been done in close contact with the requirements of the project, it provides an overview wide enough for providing a state of the art in integration strategies between CBR and MBR technologies.Postprint (published version