COSC2636/2632: Big Data Management - Billboards Within the Budget Report Writing - IT Assignment Help

Assignment Task:

1. Overview 

Problem Description: Given a set of existing routes in a social network, a passenger wants to go from source A to destination B, your need to implement a method to return the k nearest direct routes (user can follow to travel from A to B) efficiently. The basic requirements are below:

1. k, A, B are arbitrary and can be input by users.

2. Using the searching idea from paper to achieve early termination, without checking all candidates in the dataset. Therefore, a brute-force method that scans all candidates is not acceptable. 

Step-by-Step Guidance to complete this assignment:

a. Read paper 

i. Section 1 to 4.1 of the paper “Searching Trajectories by Locations – An Efficiency Study”, which is introduced in both the lecture and tutlab.

ii. Understand the input, output and search paradigm (Algorithm 1).

iii. Familiar with the operations of R-tree (which you have learnt in lecture 2-3 and tutorial & lab in the first 5 weeks).

b. Have a look at the LA trajectory dataset (available at /index/la_trips.txt in the IKNN code package).

c. Understand how to store and index trajectories. 

i. Store trajectory as points.

ii. Create R-tree index based on all the points (see /index/la_points.txt in the IKNN code package).

iii. Building a mapping table to show the relationships between point and trajectory. (can be maintained in the main memory)

d. How to search k nearest routes by a pair of points? 

i. How to compute the distance from the query to the route?

ii. Build spatial index.

iii. Filter impossible routes in advance based on the bound comparison.

iv. Refine the remaining candidate routes. 

Requirement: 

Note that in this assignment, we provide most part of the code, and what you need to implement is actually d(iii) and d(iv) highlighted above (details are in Sec 4.1 of the paper). The code skeleton is located in the path (i.e., src/rmit/IKNN.java). What you need to do: (1) understand the code skeleton and the function of each API; (2) implement the core functions in “IKNN.java”; (3) after you finish all the codes, run the “src/rmit/Test.java” with correct input formats to check the program. 

Before implementing the code: You need to create a database to insert all trajectories to a database, for later use at “refinement” step (step d(iv)) the points of dataset. Here, we give the following guidance on how to do the insertion of data. 1. Install MySQL 2. Run SQL file in the db folder “src/db/tb_la_dataset.sql”. 3. Change the setting in Settings.java. 

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