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Classifying and mapping e-Tourism data sets
The scope of the thesis is to apply text mining techniques to classify e-tourism data sets. These sets are hotel descriptions, each description consisting of a set of given attributes (usually Boolean attributes following the so-called GIATA standard) and a free text.
In a first step, these descriptions need to be analyzed and harmonized (on a semantic/conceptual as well as schema level). In a next step the tourism objects need to by classified, using both the set of attributes as well as the textual descriptions. In the latter case text mining techniques should be applied. In a final step these classified tourism objects should be mapped to the “harmonized” data schema. In such a way objects can be easily exchanged between different parties. Web Services should be developed to demonstrate the proof-of-concept. The evaluation is based on real world data. Thorough skills in text mining, Java and Web Services are required. Co-supervisor: Dr. Rainer Schuster.
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