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Variations in Greedy Approach to Set Covering Problem

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  • Mon, 07/09/2018 - 2:00pm - 4:00pm




Variations in Greedy Approach to Set Covering Problem

MSc Thesis Proposal by:

Shreeya Singhania

Date:  Monday, July 9th, 2018
Time:  2:00 pm – 4:00 pm
Location: 3105, Lambton Tower

Abstract: The weighted set covering problem is to choose a number of subsets to cover all the elements in a universal set at the lowest cost. It is a well-studied classical problem with applications in various fields like machine learning, planning, information retrieval, facility allocation, etc. Deep web crawling refers to the process of gathering documents that have been structured into a data source and can be retrieved through a search interface. Its query selection process calls for an efficient solution to the set covering problem. Within this context, the data follows the lognormal and power law distribution, and a TS-IDS algorithm has been proposed in the literature and demonstrated to outperform both the greedy and IDS algorithm. We propose to evaluate the performance of various greedy approaches to the set covering problem, including the TS-IDS, using open source dataset in the context of resource management. The data will be sampled from a given roadmap with different coverage radius.

Thesis Committee:
Internal Reader: Dr. Jianguo Lu
External Reader: Dr. Huapeng Wu
Advisor: Dr. Jessica Chen

 



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