spell check done

diff --git a/thesis2/3.methods.tex b/thesis2/3.methods.tex
index a30dcbe..9a458b0 100644 (file)
--- a/thesis2/3.methods.tex
+++ b/thesis2/3.methods.tex
@@ -2,7 +2,7 @@
 The backend consists of several processing steps that the input has go through
 before it is converted to a crawler specification. These steps are visualized
 in Figure~\ref{appinternals}. All the nodes are important milestones in the
 The backend consists of several processing steps that the input has go through
 before it is converted to a crawler specification. These steps are visualized
 in Figure~\ref{appinternals}. All the nodes are important milestones in the

-process of processing the user data. Arrows indicate informatio transfer
+process of processing the user data. Arrows indicate information transfer

 between these steps. The Figure is a detailed explanation of the
 \textit{Backend} node in Figure~\ref{appoverview}.
 
 between these steps. The Figure is a detailed explanation of the
 \textit{Backend} node in Figure~\ref{appoverview}.
 


@@ -14,12 +14,12 @@ between these steps. The Figure is a detailed explanation of the
 \end{figure}
 
 \section{HTML data}
 \end{figure}
 
 \section{HTML data}

-The raw data from the Frontend with the user markings enter the backend as a
+The raw data from the frontend with the user markings enter the backend as a

 HTTP \textit{POST} request. This \textit{POST} request consists of several
 information data fields. These data fields are either fields from the static
 description boxes in the frontend or raw \textit{HTML} data from the table
 showing the processed RSS feed entries which contain the markings made by the
 HTTP \textit{POST} request. This \textit{POST} request consists of several
 information data fields. These data fields are either fields from the static
 description boxes in the frontend or raw \textit{HTML} data from the table
 showing the processed RSS feed entries which contain the markings made by the

-user. The table is sent in whole precicely at the time the user presses the
+user. The table is sent in whole precisely at the time the user presses the

 submit button. Within the \textit{HTML} data of the table markers are placed
 before sending. These markers make the parsing of the tables more easy and
 remove the need for an advanced \textit{HTML} parser to extract the markers.
 submit button. Within the \textit{HTML} data of the table markers are placed
 before sending. These markers make the parsing of the tables more easy and
 remove the need for an advanced \textit{HTML} parser to extract the markers.


@@ -109,7 +109,7 @@ be found in Listing~\ref{pseudodawg} named as the function
 in Listing~\ref{dawg.py}.
 \begin{enumerate}
        \item 
 in Listing~\ref{dawg.py}.
 \begin{enumerate}
        \item 

-               Say we add word $w$ to the grahp. Step one is finding the
+               Say we add word $w$ to the graph. Step one is finding the

                common prefix of the word already in the graph. The common
                prefix is defined as the longest subword $w'$ for which there
                is a $\delta^*(q_0, w')$. When the common prefix is found we
                common prefix of the word already in the graph. The common
                prefix is defined as the longest subword $w'$ for which there
                is a $\delta^*(q_0, w')$. When the common prefix is found we

diff --git a/thesis2/4.discussion.tex b/thesis2/4.discussion.tex
index 5e3d10d..6bce1a0 100644 (file)
--- a/thesis2/4.discussion.tex
+++ b/thesis2/4.discussion.tex
@@ -49,7 +49,7 @@ feeds text fields. The algorithm is designed to detect and extract information
 via patterns in plain text and the performance on HTML is very bad compared to
 plain text. A text field with HTML is almost useless to gather information
 from because they usually include all kinds of information in other modalities
 via patterns in plain text and the performance on HTML is very bad compared to
 plain text. A text field with HTML is almost useless to gather information
 from because they usually include all kinds of information in other modalities

-then text. Via a small study on a selecteion of RSS feeds($N=10$) we found that
+then text. Via a small study on a selection of RSS feeds($N=10$) we found that

 about $50\%$ of the RSS feeds misuse the protocol in such a way that extraction
 of data is almost impossible. This reduces the domain of good RSS feeds to less
 then $5\%$ of the venues.
 about $50\%$ of the RSS feeds misuse the protocol in such a way that extraction
 of data is almost impossible. This reduces the domain of good RSS feeds to less
 then $5\%$ of the venues.