Introduction :

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Data mining method is used commonly to analyse huge amount of data and extract unforeseen results from that data. Data mining techniques are used in a wide variety of disciplines and fields such as tourism and hospitality, customer relationship management in marketing, medical disease prediction and etc.

Tourism and hospitality is one of the most important points of service industry. For example, guest review is very important in hospitality industry. It reveals all the aspects of the hotel profiles, no matter is good or bad. We may use data mining to find the hidden pattern and relationship that may help in our field of research. Tourism business may benefit from data mining techniques to create customer-based business mind. By using data mining application, businessman in tourism industry will be able to conduct detail analysis to have a better understanding of customer’s profile and their needs in order to offer and arrange the best service for them.

For example, positive review boosts the occupancy rate and generate higher revenue since more people will want to stay at your hotel after reading the positive review. So, there is need to apply data mining by using the review given by the customer to conduct detail analysis to have a better understanding of customer profile and their needs in order to offer and arrange the best service for them.

In this study, it is aimed to prove that data mining methods can be used effectively in tourism industry in order to increase service quality and meet the customer demands.

Scenarios:

1. Hospitality is the feeling and relationship between a guest and a host. Choosing the right and suitable hotel has been a big problem for every traveler a long time, even some information the hotel management provided on their official website can be unreal and misleading.

​2. It’s hard for most traveler to figure out which is the best or more comfortable hotel to stay, especially, when you are totally new to an unknown place without any local friends, the feeling would be bummed.

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Benefits:

1. It is buys’ market. Due to the difficulty of choosing hotel based on luck or their own untrusted information, we can figure out the hotel rating based on the previous customers’ reviews using data mining tools. These tools recommend you the suitable hotel based on your choosing attributes or features of the hotel. It is not sellers’ market anymore in the tourism industry, travelers are able to choose the hotel they wish to live in. They won’t be rushed to check-in available hotel anymore.
2. It is totally hassling free. Traveler no longer have to collect and compare information on themselves, all the steps will be done on their single click with our hotel recommend system.
3. It is time saving. Once traveler decide destination, they are able to go travelling based on the information given.

4. It is trusted. All the ratings are based on real information and reviews from the previous customers.

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Objective:
The main objective of this research work is to prove that data mining method can be used effectively in tourism industry in order to increase service quality and meet the customer demands.

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Data Mining Task:
1) Prediction :
• To determine the rating when a location is recommended to a tourist club member
2) Clustering :
• To determine which tour group is suitable to a new member based on her past location ratings.
• To provide benefits of grouping the customers to aid hoteliers in understanding customers.
3) Association rules, Clustering, Classification :
• To determine the best location to be recommended to a tourist club member.
4) Classification :
• To classify valuable travelers and predicting their future destinations.

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News : The use of Social Media and Internet Data-Mining for the Tourist Industry

There are three main methods and procedures of use of data mining in tourism industry which is forecasting expenses on tourism, analysis of the tourist profile as a target group and forecasting the number of tourist arrivals.

 

News : Application of Data Mining Techniques for Tourism Knowledge Discovery

Based on this article, it explained about extract important insights from tourism data can be experimented by application of five implementations of three data mining classification techniques. In order to find out the best performing algorithm among the compared ones for tourism knowledge discovery. It states that several emerging applications in information-providing services require for various data mining techniques to better understand user behaviour, to improve the service provided and to increase business opportunities.

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Academic Paper : Data Mining in Tourism

According to the MIS Class Blog by Billy S., he states that data mining can provide accurate data and information for the tourism industry in order to can get quick and up to date information from many locations around the world.

 

Academic Paper : Applying Data Mining to Analyse Travel Pattern in searching Travel Destination Choices

Through tourism industry using data mining tools it can be able to define marketing strategies, provide more affordable products and services for tourist who have various lifestyle. The literature review state that data mining is a business process and information filter process to find out huge amounts of data by using certain technique methods which can improve and understand to use the data. Also have describes the Knowledge Discovery in Database process which is a discovery method to computes and evaluates patterns on the way to be transformed into knowledge.

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