Mining the data from the
huge collection that are present in the database and uncovering the
relationships between the item set are one of the key aspects of data mining
technologies. Itinerary planning system with personalization in selecting the
places to the users is one of the demanding features in most of the travel
plan. In this work, the system is designed in such a way to provide the
customized journey plan to the users and also the effective one to the back
pack travelers. Here the Points of Interests are the places to visit in each
destination for the number of days chosen by the travelers. In this system, the
users are allowed to specify the desired POIs to visit for the selected
destination and can make their customized travel plan effectively. This
proposed system is designed to choose the customized places to visit and to
plan travel for K-day itineraries. The most visited itineraries are saved and
updated in the database. Association rules are used to find out the frequent
places visited in each destination and to provide the reputed places to the
users to plan the journey. Here the Weka tool is used to evaluate the
performance of the algorithm and the rules that are generated for the given
travel dataset. Data set is designed by considering several attributes that can
take part during travel such as source, destination, travel cost, budget, etc.
Statistical analysis is done to evaluate the performance of the proposed system
and the list of features that are present in the system. During the analysis
part, registered users, number of logins, frequent visits, and attributes are
analyzed. Thus the system can be redefined further with the help of this
statistical analysis. It is mostly used at the organization end to evaluate
their performance and improve the features. Report is generated once the user
has chosen their customized places to visit and all detailed description of
journey is presented to the user. Report could be saved at the user end and
they can use it for the future reference. Thus the goal of the system is to
provide the customized travel with personalization in choosing POIs and to find
the frequent places visited with desired amenities.
References
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