update send franc

diff --git a/thesis2/1.introduction.tex b/thesis2/1.introduction.tex
index 2aae8a6..3efa80b 100644 (file)
--- a/thesis2/1.introduction.tex
+++ b/thesis2/1.introduction.tex
@@ -48,7 +48,7 @@ information so that the information will appear structured in the
 expensive.
 
 The program is built so that a programmer can easily add fields or categories
 expensive.
 
 The program is built so that a programmer can easily add fields or categories

-to the data to make it flexible for changes. 
+to the application to reduce programming costs and complex modifications.

 
 \section{Why RSS/Atom}
 Information from venues comes in various different format with for each format
 
 \section{Why RSS/Atom}
 Information from venues comes in various different format with for each format


@@ -72,7 +72,9 @@ data are static and mainly only usable by computer science experts. 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.
 
 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.
 

-The project is a continuation of the past project done by Roelofs et
-al.\cite{Roelofs2009}. The techniques described by Roelofs et al. are more
-focussed on extracting data from websites and/or already isolated data so it
-can be an addition to the current project.
+The project is a side project of the past project done by Roelofs et
+al.\cite{Roelofs2009}. Roelofs et al. describes a technique to recognize date
+strings using an adapted Levensteins algorithm. This technique can be fitted in
+the current project because it works on a low level and the technique we
+describe works on a high level. The algorithm only works on already isolated
+data.

diff --git a/thesis2/2.methods.tex b/thesis2/2.methods.tex
index 9df1941..db5e56c 100644 (file)
--- a/thesis2/2.methods.tex
+++ b/thesis2/2.methods.tex
@@ -22,7 +22,6 @@ Generate xml
 \section{Crawler application}
 \subsection{Interface}
 
 \section{Crawler application}
 \subsection{Interface}
 

-\subsection{Algorithm}

 \subsection{Preprocessing}
 When the data is received by the crawler the data is embedded as POST data in a
 HTTP request. The POST data consists of several fields with information about
 \subsection{Preprocessing}
 When the data is received by the crawler the data is embedded as POST data in a
 HTTP request. The POST data consists of several fields with information about


@@ -56,7 +55,7 @@ and intermediate states are marked with a single circle.
        \caption{Sample DAG}
        \label{fig:f21}
        \centering
        \caption{Sample DAG}
        \label{fig:f21}
        \centering

-       \digraph[]{graph2}{
+       \digraph[]{graph21}{

                rankdir=LR;
                1, 2 [shape="circle"];
                3, 4 [shape="doublecircle"];
                rankdir=LR;
                1, 2 [shape="circle"];
                3, 4 [shape="doublecircle"];


@@ -66,6 +65,87 @@ and intermediate states are marked with a single circle.
        }
 \end{figure}
 
        }
 \end{figure}
 

-Using the algorithm described by Hopcroft et al\cite{Hopcroft1971} the
-nodelists are converted into minimal directed acyclic graphs with a low
-complexity($\mathcal{O}(N\log{N})$).
+The first algorithm to generate DAG's was proposed by Hopcroft et
+al\cite{Hopcroft1971}. The algorithm they described wasn't incremental and had
+a complexity of $\mathcal{O}(N\log{N})$. \cite{Daciuk2000} et al. later
+extended the algorithm and created an incremental one without increasing the
+computational complexity. The non incremental algorithm from Daciuk et al. is
+used to convert the nodelists to a graph.
+
+For example constructing a graph that from the entry: \textit{a,bc} and
+\textit{a.bc} goes in the following steps:
+
+\begin{figure}[H]
+       \caption{Sample DAG, first entry}
+       \label{fig:f22}
+       \centering
+       \digraph[]{graph22}{
+               rankdir=LR;
+               1,2,3,5 [shape="circle"];
+               5 [shape="doublecircle"];
+               1 -> 2 [label="a"];
+               2 -> 3 [label="."];
+               3 -> 4 [label="b"];
+               4 -> 5 [label="c"];
+       }
+\end{figure}
+
+\begin{figure}[H]
+       \caption{Sample DAG, second entry}
+       \label{fig:f23}
+       \centering
+       \digraph[]{graph23}{
+               rankdir=LR;
+               1,2,3,5,6 [shape="circle"];
+               5 [shape="doublecircle"];
+               1 -> 2 [label="a"];
+               2 -> 3 [label="."];
+               3 -> 4 [label="b"];
+               4 -> 5 [label="c"];
+
+               2 -> 6 [label=","];
+               6 -> 4 [label="b"];
+       }
+\end{figure}
+
+\subsection{Defining categories}
+pass
+
+\subsection{Process}
+Proposal was written
+
+
+First html/mail/fax/rss, worst case rss
+
+
+After some research and determining the scope of the project we decided only to
+do RSS, this because RSS tends to force structure in the data because RSS feeds
+are often generated by the website and thus reliable and consistent. We found a
+couple of good RSS feeds.
+
+
+At first the general framework was designed and implemented, no method yet.
+
+
+Started with method for recognizing separators.
+
+
+Found research paper about algorithm that can create directed acyclic graphs
+from string, although it was designed to compress word lists it can be
+(mis)used to extract information.
+
+
+Implementation of DAG algorithm found and tied to the program.
+
+
+Command line program ready. Conversation with both supervisors, gui had to be
+made.
+
+Step by step gui created. Web interface as a control center for the crawlers.
+
+
+Gui optimized.
+
+
+Concluded that the program doesn't reach wide audience due to lack of well
+structured rss feeds.

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diff --git a/thesis2/thesis.bbl b/thesis2/thesis.bbl
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+\begin{thebibliography}{1}
+
+\bibitem{Daciuk2000}
+Jan Daciuk, Stoyan Mihov, Bruce~W. Watson, and Richard~E. Watson.
+\newblock {Incremental Construction of Minimal Acyclic Finite-State Automata}.
+\newblock {\em Computational Linguistics}, 26(1):3--16, March 2000.
+
+\bibitem{Hopcroft1971}
+John Hopcroft.
+\newblock {An N log N algorithm for minimizing states in a finite automaton}.
+\newblock Technical report, 1971.
+
+\bibitem{Roelofs2009}
+Wouter Roelofs, Alessandro~Tadeo Paula, and Franc Grootjen.
+\newblock {Programming by Clicking}.
+\newblock In {\em Proceedings of the Dutch Information Retrieval Conference},
+  pages 2--3, 2009.
+
+\end{thebibliography}

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