Marketing management employs various tools and techniques, including market research, to perform accurate marketing analysis. Information and communication technology provided a new dimension in marketing research to maximise the revenues and profits of the firm by identifying the chief attributes affecting decisions. In this paper, we present a hybrid approach for attribute selection in marketing based on rough computing and formal concept analysis. Our approach is aimed at handling an information system that contains numerical attribute values that are “almost similar” instead of “exact similar”. To handle such an information system we use two processes—pre-process and post-process. In pre-process, we use rough set on intuitionistic fuzzy approximation space with ordering rules to find knowledge and associations, whereas in post-process we use formal concept analysis to identify the chief attributes affecting decisions. © 2017

Debi Prasanna Acharjya

Department of Computational Intelligence

School of Computer Science and Engineering

Vellore Campus

Tapan Kumar Das

Department of Digital Communications

School of Information Technology and Engineering

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

IIMB Management Review

The growth of information and communication technology makes people neglect their cultural heritage due to various factors, and it leads to a lack of cultural heritage transformation from one generation to the next generation. It greatly impacts on pilgrimage attitude towards cultural heritage. Besides, the expansion of heritage places improves the economic worth of any nation. Further, pilgrimage attraction is a major concern, which in turn improves the business opportunities. In general, cultural heritage depends on the historical, aesthetic, and architectural value of a particular place. Apart from these factors, some other parameters are also associated with cultural heritage. Therefore, it is significant to understand the behavioral pattern of the pilgrimage and their likeliness. This paper makes a phenomenological approach to uncover subliminal values associated with the cultural heritage places of Odisha, India. The prime objective is to study the attitude of pilgrimage towards visiting cultural heritage places. The attitude of pilgrimage depends on different dimensions, such as historical, aesthetic, architectural, spiritual, environment, economic, and management. Looking into uncertainty and frequent changes in human behavior, we employ variance-based structural equation modeling using partial least square and rough set for analyzing the information system. Variance-based structural equation modeling using partial least square help us to identify the factors that are essential for the study, and then the rough set is used to generate the rules. It, in turn, study the attitude of pilgrimage towards cultural heritage place of Odisha. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature.

Journal of Ambient Intelligence and Humanized Computing

An integrated partial least square and rough set approach for studying pilgrimage attitude towards cultural heritage of Odisha

Hospital ranking is a cumbersome task, as it involves dealing with a large volume of underlying data. Rankings are usually accomplished by comparing different dimensions of quality and services. Even the quality care measurement of a hospital is multi-dimensional: It includes the experience of both clinical care and patient care. In this research, however, the authors focus on ratings based only on customer perception. A framework which consists of two stages—Stage I and Stage II—is designed. In the first stage, the model uses a rough set in a fuzzy approximation space (RSFAS) technique to classify the data; whereas in the second stage, a fuzzy soft set (FSS) technique is employed to generate the rating score. The model is employed for comparing USA hospitals by region using annual HCAHPS survey data. This article shows how ranking of the healthcare institutions can be carried out using the RSFAS (rough set in a fuzzy approximation space) and fuzzy soft set techniques.

International Journal of Healthcare Information Systems and Informatics

A Framework for Ranking Hospitals Based on Customer Perception Using Rough Set and Soft Set Techniques

Large volumes of raw data are created from the digital world every day. Acquiring useful information from these data is challenging, and it turned into a prime zone of momentum explore. More research is done in this direction. Further, in disease diagnosis, many uncertainties are involved in the information system. To handle such uncertainties, intelligent techniques are employed. In this paper, we present an integrated scheme for heart disease diagnosis. The proposed model integrates cuckoo search and rough set for inferencing decision rules. At the underlying phase, we employ a cuckoo search to discover the main features. Further, these main features are analyzed using rough set generating rules. An empirical analysis is carried out on heart disease. Besides, a comparative study is also presented. The comparative study demonstrates the feasibility of the proposed model.

Journal of Medical Systems

A Hybrid Scheme for Heart Disease Diagnosis Using Rough Set and Cuckoo Search Technique

Behavioural finance has gained research interest among researchers because of investor behavior and market anomalies. Investor behaviour varies with demographics and geographic characteristics. Further, investor behavior towards a gold exchange trade fund is gaining research interest due to various factors. Not much research has been carried out in this direction, with the exception of some comparisons. Therefore, the performance of a gold exchange traded fund needs to be assessed from the investor behavior perspective. Additionally, the investors behavior contains uncertainties. Thus, there is a need for intelligent techniques for identifying the investors behavior despite the presence of uncertain behavioral characteristics. Therefore, to study uncertain behavior characteristic in gold exchange traded fund, in this article the authors employ a fuzzy rough set. They employ fuzzy rough quick reduct algorithm to find the superfluous attributes. Further decision rules are generated to identify the chief feature of investors' behavior towards gold exchange traded fund.

International Journal of Business Analytics

A Fuzzy Rough Feature Selection Framework for Investors Behavior Towards Gold Exchange-Traded Fund

The amount of data collected across various sources in real life situations is never in its complete form. That is, it is never precise or it never gives definite knowledge. It always contains uncertainty and vagueness. Therefore, most of our traditional tools for formal modelling, reasoning and computing can not handle efficiently. Therefore, it is very challenging to organize this data in formal system which provides information in more relevant, useful, and structured manner. There are many techniques available for knowledge extraction form this high dimensional data. This chapter discusses various rough computing based knowledge extraction techniques to obtain meaningful knowledge from large amount of data. A real life example is provided to show the viability of the proposed research.

Improving Knowledge Discovery through the Integration of Data Mining Techniques Advances in Data Mining and Database Management

Knowledge Extraction from Information System Using Rough Computing

2006 3rd International IEEE Conference Intelligent Systems

Rough Sets on Intuitionistic Fuzzy Approximation Spaces

Using an illustrative case study on the Indian cosmetic industry, this paper illustrates the advantages of the rough set approach over conventional techniques for the extraction of decision rules from data sets, which can be useful in various marketing applications. The rule generated through the methodology can act as an ‘expert’, which may be referred to in future strategic decision-making. The approach gives results similar to the results obtained through statistical methods but without making any assumption.

Journal	Data powered by TypesetIIMB Management Review
Publisher	Data powered by TypesetElsevier BV
ISSN	0970-3896
Open Access	Yes