Journal ArticleDOI
Rough Clustering of Destination Image Data Using an Evolutionary Algorithm
TLDR
The article describes the template, the data structure used to describe rough clusters, and provides an overview of the evolutionary algorithm used to develop viable cluster solutions, consisting of an optimal number of templates, which provide easily interpreted descriptions of the clusters.Abstract:
This article describes a hybrid computational intelligence technique, an evolutionary algorithm based rough clustering algorithm. The technique of cluster analysis is fundamental in traditional data analysis and data mining, and is used to group similar objects together. Many clustering methods have been identified, including the commonly used k-means approach, which is dependent on initial starting points and requires the number of clusters to be specified in advance. The rough clustering algorithm described in this article is able to overcome these limitations. Rough clusters are defined in a similar manner to the rough set concept developed by Pawlak—that is, using a lower and upper approximation. This allows for multiple cluster membership for objects in the data set. The lower approximation of a rough cluster contains objects that only belong to that cluster. The upper approximation of a rough cluster contains objects that belong to more than one cluster. The article describes the template, ...read more
Citations
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Journal ArticleDOI
Destination image: a meta-analysis of 2000-2007 research.
TL;DR: A comprehensive review of conceptual and empirical research on destination image published between January 2000 and October 2007 is provided with the aim of identifying current and emerging trends in the area of destination image studies.
Journal ArticleDOI
Identifying changes and trends in Hong Kong outbound tourism
TL;DR: In this article, a new approach that extends the capability of the association rules technique to contrast targeted association rules with the aim of capturing the changes and trends in outbound tourism is presented.
Journal ArticleDOI
Positioning and clustering of the world’s top tourist destinations by means of dimensionality reduction techniques for categorical data
Oscar Claveria,Alessio Poluzzi +1 more
TL;DR: In this paper, a study aims to cluster the world's top tourist destinations based on the growth of the main tourism indicators over the period between 2000 and 2010, and ranks the destinations with respect to the average growth rate over the sample period.
Journal ArticleDOI
Tourism-Receiving Countries in Connotative Google Space
TL;DR: Visualizing the destination countries’ similarity in terms of Web-projected connotative profiles highlights one aspect of competitive threat.
Journal ArticleDOI
Positioning emerging tourism markets using tourism and economic indicators
TL;DR: In this paper, the authors focus on the interactions between tourism and economic variables in twenty emerging markets and provide a descriptive analysis and rank the countries according to their percentage average annual growth in relation to a set of economic and tourism indicators during the last decade.
References
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Book
Computational Intelligence: An Introduction
TL;DR: Computational Intelligence: An Introduction, Second Edition offers an in-depth exploration into the adaptive mechanisms that enable intelligent behaviour in complex and changing environments, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation.
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Artificial Intelligence: A Guide to Intelligent Systems
TL;DR: The book demonstrates that most ideas behind intelligent systems are simple and straightforward, and the reader needs no prerequisites associated with knowledge of any programming language.
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A review and meta-analysis of country-of-origin research
TL;DR: This article conducted a quantitative meta-analysis of country-of-origin effects on three types of product evaluations, viz., perceived quality, attitude, and purchase intention, and found that country of origin has a larger effect on perceived quality than on attitude toward the product or purchase intention.
BookDOI
Rough Sets and Current Trends in Computing
Journal ArticleDOI
A Proposal for the Dartmouth Summer Research Project on Artificial Intelligence, August 31, 1955
TL;DR: The 1956 Dartmouth summer research project on artificial intelligence was initiated by this August 31, 1955 proposal, authored by John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon, along with the short autobiographical statements of the proposers.
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Robust Rough-Fuzzy C-Means Algorithm: Design and Applications in Coding and Non-coding RNA Expression Data Clustering
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