Using Support Vector Machines to classify unwanted content on the internet

Slot, V. (2012) Using Support Vector Machines to classify unwanted content on the internet. Bachelor's Thesis, Artificial Intelligence.

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Abstract

Every day it is getting harder to find the correct information on the internet. The amount of web pages has taken on huge proportions, for private use, but also for businesses large and small. For this reason companies might choose to deploy a custom made search engine. In this way they can keep the content on their servers easily accessible for their clients. To keep the search engine database as small as possible we used a machine learning tool based on Support Vector Machines to filter out any unwanted content that is considered to be entered in the database. This filter will increase the efficiency of processing search queries on the servers containing the databases. In this paper the algorithm will be explained and evaluated to decide whether or not it satisfies the demands and standards of today's commercial search engine providers.

Item Type:	Thesis (Bachelor's Thesis)
Degree programme:	Artificial Intelligence
Thesis type:	Bachelor's Thesis
Language:	English
Date Deposited:	15 Feb 2018 07:50
Last Modified:	15 Feb 2018 07:50
URI:	https://fse.studenttheses.ub.rug.nl/id/eprint/10389

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