The tourism among the riparian Black Sea countries

• Author: Petcu, N.
• Position: Dept. of Management and Economic Informatics, Transilvania University of Brasov
• Pages: 103-108

Bulletin of the Transilvania University of Braşov • Vol. 6 (55) •No. 1 - 2013

Series V: Economic Sciences

THE TOURISM AMONG

THE RIPARIAN BLACK SEA COUNTRIES

Nicoleta PETCU

1

Abstract: The industry of tourism and travelling is nowadays the most

dynamic field worldwide, thus being the most important job generator. From

an economic point of view, tourism is also a main sour ce of recovery of the

nationa l economies of those countries tha t have importa nt tourist resources

and exploit them accordingly. Its action develops on more plans, star ting

with stimulating economic d evelopment to improving socia l structur e, with

the superior capitalization of resour ces to the improvement of life conditions.

This work aims at the i mplementation of the multi-dimensional an alysis

methods: main components ana lysis, cluster analysis, rela tive distances

method to establish Romanian’s place a mong the countries with harbour to

the Black Sea, on the basis of the tourism indicators.

Key words: relative distances method, main components analysis, cluster

ana lysis.

1 Dept. of Management and Economic Informatics, Transilvania University of Braşov.

1. Introduction

Data Mining (the analysis step of the

Knowledge Discovery in Databases

process, or KDD) Fayyad, Usama;

Gregory Piatetsky-Shapiro, and Padhraic

Smyth (1996), a relatively young and

interdisciplinary field of computer science,

is the process of discovering new patterns

from large data sets involving methods

from statistics and artificial intelligence

but also database management. The actual

data mining task is the automatic or semi-

automatic analysis of large quantities of

data in order to extract previously

unknown interesting patterns such as

groups of data records: cluster analysis

Agrawal, R.; Gehrke, J.; Gunopulos, D.;

Raghavan, P. (2005) unusual records -

anomaly detection, Hans-Peter Kriegel,

Peer Kröger, Arthur Zimek (2009,

dependencies - association rule mining,

Varun Chandola, Arindam Banerjee, and

Vipin Kumar(2009)) and decision support

system, Keen (1978).

Methods: Cluster analysis or

clustering is the task of assigning a set of

objects into groups (called clusters) so that

the objects in the same cluster are more

similar (in some sense or another) to each

other than to those in other clusters.

A decision tree is a decision support tool

that uses a tree-like graph or model of

decisions and their possible consequences,

including chance event outcomes, resource

costs, and utility. It is a way to display an

algorithm. Decision trees are commonly

used in operations research, specifically in

decision analysis, to help identify a

strategy most likely to reach a goal.

Another use of decision trees is as a

descriptive means for calculating

conditional probabilities.

In statistics, regression analysis includes

any techniques for modelling and