Determination of attributes affecting price-performance using fuzzy rule-based systems: online ratings of hotels by travel 2.0 users

2020 ◽  
Vol 11 (2) ◽  
pp. 291-311
Author(s):  
Seden Doğan ◽  
Murat Alper Basaran ◽  
Kemal Kantarci
Keyword(s):  
Fuzzy Rule ◽  
Data Set ◽  
Rule Based ◽  
Content Type ◽  
Rule Based System ◽  
Price Performance ◽  
Soft Computing Method ◽  
Online Ratings ◽  
German Speaking ◽  
Overall Evaluation

Purpose Fuzzy rule-based system (FRBS), a soft computing method used for big data analysis, is used to determine which single hotel attribute or interrelated hotel attributes used in Travel 2.0 data play a role on price–performance (PP). Design/methodology/approach FRBS, based on fuzzy set theory, is used using the data set of four- and five-star hotels in the Alanya destination in Turkey collected from HolidayCheck.de website for the period between 2009 and 2016. Findings Single attributes do not have an impact on PP. At least two or more attributes are necessary to have an impact on PP. Compensations among attributes that are observed to be leading to PP not to change from their current level. Instead of assuming a linear relationship between hotel attributes and PP, non-linearity should often be assumed. In addition, some hotel attributes do not have an impact on PP until some other attribute reaches a certain level. Research limitations/implications The limitations of this research can be grouped under two topics. While the first is related to data, which is German-speaking tourists staying at four- and five-star hotels between 2009 and 2016, the second is the limitation on generalizability. By implementing other types of data related to hotel attributes, new insights can be generated to shed light on different aspects of the relationship between hotel attributes and PP or other measures such as overall evaluation. Originality/value A data-driven model called FRBS is constructed using original verbal statements. Novel insights pertinent to relations between hotel attributes and PP have been extracted.

A fuzzy rule-based system to assess e-government technical interoperability maturity level

2014 ◽  
Vol 8 (3) ◽  
pp. 335-356 ◽  
Author(s):  
Andreiwid Sheffer Corrêa ◽  
Alexandre de Assis Mota ◽  
Lia Toledo Moreira Mota ◽  
Pedro Luiz Pizzigatti Corrêa
Keyword(s):  
Fuzzy Rule ◽  
Assessment Process ◽  
Maturity Model ◽  
Maturity Level ◽  
Rule Based ◽  
Content Type ◽  
Management Level ◽  
Rule Based System ◽  
Brazilian Government ◽  
Information And Communication

Purpose – The purpose of this study is to present a system called NEBULOSUS, which is a fuzzy rule-based expert system for assessing the maturity level of an agency regarding technical interoperability. Design/methodology/approach – The study introduces the use of artificial intelligence and fuzzy logic to deal with the imprecision and uncertainty present in the assessment process. To validate the system proposed and demonstrate its operation, the study takes into account the Brazilian technical interoperability maturity model, based on the Brazilian Government Interoperability Framework (GIF). Findings – With the system proposed and its methodology, it could be possible to increase the assessment process to management level and to provide decision-making support without worrying about technical details that make it complex and time-consuming. Moreover, NEBULOSUS is a standalone system that offers an easy-to-use, open and flexible structuring database that can be adapted by governments throughout the world. It will serve as a tool and contribute to governments’ expectations for continuous improvement of their technologies. Originality/value – This study contributes toward filling a gap in general interoperability architectures, which is a means to provide an objective method to evaluate GIF adherence by governments. The proposed system allows governments to configure their technical models and GIF to assess information and communication technology resources.

On modeling of responses generated by travel 2.0 implementation: fuzzy rule-based systems

2020 ◽  
Vol 32 (4) ◽  
pp. 1503-1522 ◽  
Author(s):  
Murat Alper Basaran ◽  
Seden Dogan ◽  
Kemal Kantarci
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Rule ◽  
Human Beings ◽  
Rule Based ◽  
Content Type ◽  
Price Performance ◽  
Single Attribute ◽  
Data Collections ◽  
Source Of Information ◽  
Rule Based Systems

Purpose Web 2.0 applications enable travelers to evaluate several services and assessment attributes. Constructed websites in several languages trigger a new way of data collections resulting in data streams leading to the accumulation of vast amounts of data, called big data. The need for analysis is in high demand. This study aims to construct a model to investigate which single attribute or interrelated ones having an impact on the performances of hotels. Design/methodology/approach The total number of 1,137 observations collected from the website HolidayCheck.de are used from the hotels in the Bavaria region in 2016. Bavaria is a region where both domestic and foreign travelers mostly prefer to visit. Fuzzy rule-based systems, which is a combination of fuzzy set theory (FST) and fuzzy logic, are used. Although the FST is used to convert linguistically expressed perceptions by travelers into mathematically usable data, fuzzy logic is used to construct a model between service attributes and price-performance (PP) to attain the set of single and interrelated attributes on the assessment of PP. Findings No single attribute plays a key role in PP assessment. However, two or more interrelated combinations have different impacts on PP. For example, when “Food—Drink” and “Room” moves together from average to good level, PP reaches the highest level of assessment. Research limitations/implications Accessibility to too much data is difficult. Practical implications A model can be continuously run so that any changes can be observed during the incoming of data. Social implications As the consumer reviews and ratings are the crucial source of information for other travelers, hoteliers must monitor and respond them on time in order to deal with the complaints. Originality/value Travelers’ perceptions or evaluations are treated with a FST that measures the impression of human beings. New modeling enables researchers to observe not only any single attribute but also interrelated ones on the PP.

CONSTRUCTING A FUZZY RULE-BASED SYSTEM USING THE ILFN NETWORK AND GENETIC ALGORITHM

2001 ◽  
Vol 11 (05) ◽  
pp. 427-443 ◽  
Author(s):  
GARY G. YEN ◽  
PHAYUNG MEESAD
Keyword(s):  
Genetic Algorithm ◽  
Incremental Learning ◽  
Fuzzy Rule ◽  
Correct Classification ◽  
Breast Cancer Data ◽  
Training Set ◽  
Data Set ◽  
Rule Based ◽  
Cancer Data ◽  
Rule Based System

In this paper, a method for automatic construction of a fuzzy rule-based system from numerical data using the Incremental Learning Fuzzy Neural (ILFN) network and the Genetic Algorithm is presented. The ILFN network was developed for pattern classification applications. The ILFN network, which employed fuzzy sets and neural network theory, equips with a fast, one-pass, on-line, and incremental learning algorithm. After trained, the ILFN network stored numerical knowledge in hidden units, which can then be directly interpreted into if-then rule bases. However, the rules extracted from the ILFN network are not in an optimized fuzzy linguistic form. In this paper, a knowledge base for fuzzy expert system is extracted from the hidden units of the ILFN classifier. A genetic algorithm is then invoked, in an iterative manner, to reduce number of rules and select only discriminate features from input patterns needed to provide a fuzzy rule-based system. Three computer simulations using a simulated 2-D 3-class data, the well-known Fisher's Iris data set, and the Wisconsin breast cancer data set were performed. The fuzzy rule-based system derived from the proposed method achieved 100% and 97.33% correct classification on the 75 patterns for training set and 75 patterns for test set, respectively. For the Wisconsin breast cancer data set, using 400 patterns for training and 299 patterns for testing, the derived fuzzy rule-based system achieved 99.5% and 98.33% correct classification on the training set and the test set, respectively.

Assessing flood vulnerability using a rule-based fuzzy system

2012 ◽  
Vol 66 (8) ◽  
pp. 1766-1773 ◽  
Author(s):  
J. Yazdi ◽  
S. A. A. S. Neyshabouri
Keyword(s):  
Fuzzy Rule ◽  
Vulnerability Analysis ◽  
Human Knowledge ◽  
Small Watershed ◽  
Flood Vulnerability ◽  
Rule Based ◽  
Rule Based System ◽  
Vulnerability Map ◽  
Flood Prone Areas

Population growth and urbanization in the last decades have increased the vulnerability of properties and societies in flood-prone areas. Vulnerability analysis is one of the main factors used to determine the necessary measures of flood risk reduction in floodplains. At present, the vulnerability of natural disasters is analyzed by defining the various physical and social indices. This study presents a model based on a fuzzy rule-based system to address various ambiguities and uncertainties from natural variability, and human knowledge and preferences in vulnerability analysis. The proposed method is applied for a small watershed as a case study and the obtained results are compared with one of the index approaches. Both approaches present the same ranking for the sub-basin's vulnerability in the watershed. Finally, using the scores of vulnerability in different sub-basins, a vulnerability map of the watershed is presented.

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