Modelling Tourist Destination Choice Using a Decision Table Induction Algorithm

2003 ◽  
Vol 35 (9) ◽  
pp. 1669-1687 ◽  
Author(s):  
Manon van Middelkoop ◽  
Aloys W J Borgers ◽  
H J P Timmermans
Keyword(s):  
The Netherlands ◽  
Empirical Data ◽  
Destination Choice ◽  
Decision Table ◽  
Tourist Destination ◽  
Rule Based ◽  
Destination Choices ◽  
Decision Tables

The authors report on the development and test of a rule-based model of tourist destination choice, using decision tables to represent the rules that specify the conditions under which particular destination choices are made. Rules are extracted from empirical data on tourist destination choice, collected in the Netherlands in 1998. The specification of the model and its performance are discussed.

FORMALIZATION AND MODELING OF RULES USING THE XTT2 METHOD

2011 ◽  
Vol 20 (06) ◽  
pp. 1107-1125 ◽  
Author(s):  
GRZEGORZ J. NALEPA ◽  
ANTONI LIGĘZA ◽  
KRZYSZTOF KACZOR
Keyword(s):  
Knowledge Representation ◽  
Decision Table ◽  
Rule Base ◽  
Levels Of Abstraction ◽  
Rule Based ◽  
Structured Design ◽  
New Knowledge ◽  
Textual Representation ◽  
Rule Bases ◽  
Decision Tables

The paper discusses a new knowledge representation for rule-based systems called XTT2. It combines decision trees and decision tables forming a transparent and hierarchical visual representation of the decision units linked into a workflow-like structure. There are two levels of abstraction in the XTT2 model: the lower level, where a single knowledge component defined by a set of rules working in the same context is represented by a single decision table, and the higher level, where the structure of the whole knowledge base is considered. This model has a concise formalization which opens up possibility of well-defined, structured design and verification of formal characteristics. Based on the visual XTT2 model, a textual representation of the rule base is generated. A dedicated engine provides a unified run-time environment for the XTT2 rule bases. The focus of the paper is on the formalization of the presented approach. It is based on the so-called ALSV(FD) logic that provides an expressive calculus for rules.

scholarly journals Social Trust, Safety and the Choice of Tourist Destination

2016 ◽  
Vol 4 (1) ◽  
pp. 1 ◽  
Author(s):  
Susanne Jensen ◽  
Gert Tinggaard Svendsen
Keyword(s):  
Legal System ◽  
Social Trust ◽  
Public Spaces ◽  
Informal Institutions ◽  
Destination Choice ◽  
Control Mechanisms ◽  
Formal Institutions ◽  
Tourist Destination ◽  
Policy Makers ◽  
Police Authority

Does social trust influence safety and tourists’ destination choice? Our claim is that the roots of safety may take two forms: either formal institutions or informal institutions. Formal institutions concern how society can build up control mechanisms through the legal system, police authority and military. The problem is that high visibility of police and military in public spaces may give the tourist the impression of an unsafe and insecure destination. Instead, social trust through self-enforcements of social norms for behaviour may be important because the informal institutions guarantee the safety of tourists (and locals) without signalling a problem with safety. Building social trust may further enhance the feeling of safety and thereby attract even more tourists. Thus, our trust-safety theory may guide the active use of social trust by tourist officials and policy makers.

Motivation and Other Considerations in Tourist Destination Choice: A Case Study of Nigeria

2004 ◽  
Vol 6 (3) ◽  
pp. 303-330 ◽  
Author(s):  
Onome Awaritefe
Keyword(s):  
Destination Choice ◽  
Tourist Destination

scholarly journals Historical Databases Now and in the Future

2021 ◽  
Vol 10 ◽  
pp. 9-12
Author(s):  
Kris Inwood ◽  
Hamish Maxwell-Stewart
Keyword(s):  
Data Structure ◽  
The Netherlands ◽  
Longitudinal Data ◽  
Practical Implementation ◽  
High Quality ◽  
Rule Based ◽  
Intermediate Data ◽  
The Future ◽  
Historical Databases ◽  
Historical Sample

Kees Mandemakers has enriched historical databases in the Netherlands and internationally through the development of the Historical Sample of the Netherlands, the Intermediate Data Structure, a practical implementation of rule-based record linking (LINKS) and personal encouragement of high quality longitudinal data in a number of countries.

scholarly journals Optimal scale combination selection for inconsistent multi-scale decision tables

2021 ◽  
Author(s):  
Yingjie Zhu ◽  
Bin Yang
Keyword(s):  
Lattice Model ◽  
Selection Model ◽  
Decision Table ◽  
Scale Selection ◽  
Multi Scale ◽  
Optimal Scale ◽  
Model Based ◽  
Positive Region ◽  
Decision Tables ◽  
Combination Selection

Abstract Hierarchical structured data are very common for data mining and other tasks in real-life world. How to select the optimal scale combination from a multi-scale decision table is critical for subsequent tasks. At present, the models for calculating the optimal scale combination mainly include lattice model, complement model and stepwise optimal scale selection model, which are mainly based on consistent multi-scale decision tables. The optimal scale selection model for inconsistent multi-scale decision tables has not been given. Based on this, firstly, this paper introduces the concept of complement and lattice model proposed by Li and Hu. Secondly, based on the concept of positive region consistency of inconsistent multi-scale decision tables, the paper proposes complement model and lattice model based on positive region consistent and gives the algorithm. Finally, some numerical experiments are employed to verify that the model has the same properties in processing inconsistent multi-scale decision tables as the complement model and lattice model in processing consistent multi-scale decision tables. And for the consistent multi-scale decision table, the same results can be obtained by using the model based on positive region consistent. However, the lattice model based on positive region consistent is more time-consuming and costly. The model proposed in this paper provides a new theoretical method for the optimal scale combination selection of the inconsistent multi-scale decision table.

Tourist destination choice

2015 ◽  
Author(s):  
Chunxiao Li
Keyword(s):  
Destination Choice ◽  
Tourist Destination

Building confidence measures for tourist destination choice

2017 ◽  
Vol 17 (1) ◽  
pp. 61-66
Author(s):  
Roberto Marmo ◽  
Rodolfo Baggio
Keyword(s):  
Destination Choice ◽  
Tourist Destination ◽  
Confidence Measures

Risk Appraisal and Risk Communication: Some Empirical Data From The Netherlands Reviewed

1995 ◽  
Vol 16 (1) ◽  
pp. 227-249 ◽  
Author(s):  
Oene Wiegman ◽  
Jan Gutteling
Keyword(s):  
The Netherlands ◽  
Risk Communication ◽  
Empirical Data ◽  
Risk Appraisal

scholarly journals Rough Set Approach to Approximation Reduction in Ordered Decision Table with Fuzzy Decision

2011 ◽  
Vol 2011 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaoyan Zhang ◽  
Shihu Liu ◽  
Weihua Xu
Keyword(s):  
Information Systems ◽  
Knowledge Discovery ◽  
Rough Set ◽  
Decision Table ◽  
Fuzzy Decision ◽  
Efficient Tool ◽  
Lower Approximation ◽  
Dominance Relations ◽  
Decision Tables

In practice, some of information systems are based on dominance relations, and values of decision attribute are fuzzy. So, it is meaningful to study attribute reductions in ordered decision tables with fuzzy decision. In this paper, upper and lower approximation reductions are proposed in this kind of complicated decision table, respectively. Some important properties are discussed. The judgement theorems and discernibility matrices associated with two reductions are obtained from which the theory of attribute reductions is provided in ordered decision tables with fuzzy decision. Moreover, rough set approach to upper and lower approximation reductions is presented in ordered decision tables with fuzzy decision as well. An example illustrates the validity of the approach, and results show that it is an efficient tool for knowledge discovery in ordered decision tables with fuzzy decision.

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