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Task : Skyline Search: Dataset: There are three datasets city 1 , city 2 , and city 3 each representing homes in the city. These
Task : Skyline Search:
Dataset: There are three datasetscity city and cityeach representing homes in
the city. These datasets contain D points and are stored in text files formatted as follows:
id x y
id x y
idn xn yn
Each line in the datasets represents a home, with x indicating the cost of the home for example, $ and y representing its size for example, square meters The goal is to apply the Skyline Search algorithm to find homes that provide the optimal balance of size and cost. This method helps to filter out properties that are either too costly or too small in comparison to other available options.
Program Design:
Select ONE dataset city city or city
Implement the following algorithms to assist users in choosing the ideal home based
on two key criteria: cost and size.
Sequential Scan Based Method: Identify the skyline by sequentially evaluating whether each node is dominated by any other nodes.
Branch and Bound Skyline BBS Algorithm: Construct an Rtree for the selected dataset. Implement the BBS algorithm with the Rtree to identify the skyline.
BBS with DivideandConquer: Firstly, divide the dataset into two subspaces based on X dimension or Y dimension then construct an Rtree for each subspace. Implement the BBS algorithm to identify the skyline in each subspace. Finally, obtain the skyline for the entire space through D dominance screening method.
Output: For each algorithm Sequential Scan, BBs Algorithm, and BBs with DivideandConquer display and output the following information into a single txt file:
The skyline results for the selected dataset, ie sequentially output each points ID xvalue, and yvalue.
The execution time taken to find the skyline for the selected dataset.
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