Data Mining Algorithm And Its Application In The Tourism Industry

As a new efficient and high-level data analysis and processing technology, data mining is developed from 1980s. It aims to extract the implicit, previously unknown, and potentially useful knowledge from voluminous, non-complete, fuzzy, stochastic data. Sequential patterns mining is an important research problem in the data mining domain, which aims to mining the frequent pattern. Classification is another important research problem and the common classification models are decision tree, neural network, genetic algorithm, rough set, statistical model etc. Now, data mining has been used in telecom, finance, busyness, weather forecast, DNA, stock market and intrusion detection etc, and it is expanding its application area. In this paper we mainly research the algorithm of sequential patterns mining and decision tree algorithm, the contents are shown as following:First, we described the background of research and pointed out its significance. The domestic and foreign situation of data mining research was analyzed from theoretical and applying aspects.Second, we deeply research the technique of sequential patterns mining. And we review the development of the sequential patterns mining. The content of the algorithms is analyzed. The disadvantages and advantages of these algorithms are compared.Third, we introduce the basic conception and the procession of classification analysis clearly. And we provide the assessment of the model of the classification andireview the present development of classification model based on decision tree. The principle and steps of decion tree analysis are clearly discribed. And we deeply research the algorithm of IDS.Forth, the ID3 algorithm is ameliorated from two aspects to improve the efficiency of the algorithm and reduce the quantity of the data to be processed and enhance the predictive ability of the algorithm and it is approved to be efficiency through a real-world application.Fifth, a tourist consume data analysis system is designed. The significance to research the consuming data of the tourists is indicated. Then the functions of this system are explained, which include data preprocessing, the outgo route analysis of the tour consumer, the consumeability of the tourism consumer. The preprocessing methods of data preprocessing module are discuss. Data mining techniques used in the outgo route analysis of the tourism consumer is sequential patterns mining and the consume ability of the tourism consumer is classification. The algorithms, which we use in these techniques, are depicted. Finally, we imply the system on the tourism consumer of Shandong and estimate the result.Finally, all the results are summarized, and the study prospect is discussed.