Web Scraping Techniques and Applications
dc.contributor.advisor | Brady, Alyce | |
dc.contributor.author | Shipp, Douglas | |
dc.date.accessioned | 2020-06-15T00:36:21Z | |
dc.date.available | 2020-06-15T00:36:21Z | |
dc.date.issued | 2019-09-01 | |
dc.identifier.uri | https://cache.kzoo.edu/handle/10920/38618 | |
dc.description | iv, 21 p. | en_US |
dc.description.abstract | Data is one of the most valuable resources in today's business world, and economists often liken the impact of oil and data. According to a May 2018 Forbes article, every day 2.5 quintillion bytes of data is created. Businesses have been placing a greater importance on data analytics in search of quicker decision making, cost-reduction, and new products or services. This paper will talk about my experience creating a web scraping application for an insurance management company. I will explain the basics of web scraping, its use cases, and popular techniques. During the summers of 2018 and 2019, I interned at Chelsea Rhone LLC in Ann Arbor, Michigan. Chelsea Rhone is an innovative insurance management company that works with over 1,000 clients. Primarily, I was a software developer focusing on front-end web development, however my day to day responsibilities often varied. This paper will first talk about web scraping as a topic and then more specifically the project that I developed for Chelsea Rhone. iv | en_US |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_US | en_US |
dc.relation.ispartof | Senior Individualized Projects. Computer Science. | |
dc.relation.ispartof | Kalamazoo College Computer Science Senior Individualized Projects Collection | |
dc.rights | U.S. copyright laws protect this material. Commercial use or distribution of this material is not permitted without prior written | |
dc.title | Web Scraping Techniques and Applications | en_US |
dc.type | Thesis | en_US |
Files in this item
This item appears in the following Collection(s)
-
Computer Science Senior Integrated Projects [250]
This collection includes Senior Integrated Projects (SIP's) completed in the Computer Science Department. Abstracts are generally available to the public, but PDF files are available only to current Kalamazoo College students, faculty, and staff.