In order to be more personalized and user-friendly, the optimization algorithms for the Trip Planner application is becoming more complicated, since increasing numbers of factors should be taken into consideration, for example the traveler's time schedule and budget, the traffic condition, as well as the weather condition. On the other hand, as the concept of data mining and knowledge management becoming more popular, it is of great significance for a Trip Planner app to dig out relevant knowledge from the database, thus offering travel recommendation to certain users.
The Trip Planner could be regarded as an input/output system, which receives information from the users as well as the Web Service, and feedback an optimized route solution. The core of the system is the optimization algorithm and the implementation of the system.
2. Interacting with the Google Map Direction API in the format of JSON or XML;
3. Designing an optimization algorithm to choose a best route for traveler, taking the context factors into consideration;
4.Using the association rules as well as Knowledge Discover in Database (KDD) to manage the trip planner data in the database, and digging out travel plan knowledge, thus offering relevant recommendation to users.
Applicant's Learning Objectives:
1. Conclude the fundamental principles of data mining techniques.
2. Construct a routing system with appropriate algorithms of data mining.
3. Design Index, Stored Procedures and Triggers to improve the system efficiency