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Data mining approach to implement a recommendation system for electronic tour guides

Publication Date
  • Memory
  • Text And Place
  • Computer Science


In this paper we consider the problem of discovering patterns generated by association rules between items in a database of locations that tourists have visited within the Manchester city centre area. The focus of the paper is on the interactive agenda offered by a tourist information system. This assist the user in the organisation of a visit or a tour by providing personalised recommendations dependent upon the calculations made by the association rule algorithm using the entries within a database of tourist attractions. The paper shows the development of a stand alone recommendation system, which uses association rule algorithm to propose and recommend any related locations that a particular tourist can visit based on the option they initially choose. This opens the door to take this implementation further to an extent where developing this system on a manufacturing scale is viable and be installed in major cities around the UK so that tourists can truly appreciate their time in cities like Manchester. Before such mass production can take place other data mining techniques such as clustering or temporal data mining are suitable extensions to such an application. This can offer further interactive options to tourists who use the application as a means of visiting major attractions and fulfilling their holidays.

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