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        \textbf{Abstract}\\
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+\section{Introduction}
+Within the entertainment business there is no consistent style of informing
+people about the events. Different venues display their, often incomplete,
+information in entirely different ways. Because of this, converting raw
+information from venues to structured consistent data is a relevant problem. 
+
+\section{HyperLeap}
+Hyperleap is a small company that is specialized in infotainment
+(information+entertainment) and administrates several websites which bundle
+information about entertainment in a ordered and complete way.  Right now, most
+of the data input is done by hand and takes a lot of time to type in.
+
+\section{Research question}
+The main research question is: \textit{How can we make an adaptive, autonomous
+and programmable data mining program that can be set up by a non IT
+professional which is able to transform raw data into structured data.}\\
+
+The practical goal and aim of the project is to make a crawler(web or other
+document types) that can autonomously gather information after it has been
+setup by a, not necessarily IT trained, employer via an intuitive interface.
+Optionally the crawler shouldn't be susceptible by small structure changes in
+the website, be able to handle advanced website display techniques such as
+javascript and should be able to notify the administrator when the site has
+become uncrawlable and the crawler needs to be reprogrammed for that particular
+site. But the main purpose is the translation from raw data to structured data.
+The projects is in principle a continuation of a past project done by Wouter
+Roelofs\cite{Roelofs2009} which was also supervised by Franc Grootjen and
+Alessandro Paula, however it was never taken out of the experimental phase and
+therefore is in need continuation. 
+
+\section{Scientific relevance}
+Currently the techniques for conversion from non structured data to structured
+data are static and mainly only usable by IT specialists. There is a great need
+of data mining in non structured data because the data within companies and on
+the internet is piling up and are usually left to catch dust.