Article ID Journal Published Year Pages File Type
4960459 Procedia Computer Science 2017 8 Pages PDF
Abstract

Tourism has been an irreplaceable part of economy growth of every country. By that factor, the authors were encouraged to build an application to serve detail information of tour destinations to provide easy preparation for travelling. The application, TripBuddy, was developed to learn user's behavior based on empiric data, which used to offer relevant destinations to certain user by using K-Means Clustering. TripBuddy is a web-based application which suggests optimal route with detail information of destinations, schedule, cost and duration to ease user's travel plan and it also gives recommendation based on user's browsing behavior

Related Topics
Physical Sciences and Engineering Computer Science Computer Science (General)
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