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\title{Neco Simonovo and Feature Type Selection for Pairwise Document Comparison}
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\subtitle{Notebook for PAN at CLEF 2013}

\author{\v{S}imon Suchomel \and Jan Kasprzak \and Michal Brandejs}
\institute{Faculty of Informatics, Masaryk University \\
{\tt\{suchomel,kas,brandejs\}@fi.muni.cz}}

\maketitle

\begin{abstract}
This paper describes approaches used for the Plagiarism Detection task in PAN 2013 international competition
on uncovering plagiarism, authorship, and social software misuse.  
We present modified three-way search methodology for Source Retrieval subtask and analyse snippet similarity performance.
The results show, that presented approach is adaptable in real-world plagiarism situations.
For the detailed comparison task, we discuss feature type selection,
global postprocessing. We have significantly improved the pairwise comparison
results with even further optimizations possible.
\end{abstract}


\section{Introduction}
In PAN 2013 competition on plagiarism detection we participated in both the Source Retrieval
and the Text Alignment subtask. In both tasks we adapted methodology used in PAN 2012\footnote{%
See \cite{pan2012} for an overview of PAN 2012 plagiarism detection campaign.} \cite{suchomel_kas_12}.
Section~\ref{source_retr} describes querying approach for source retrieval, where we used three different 
types of queries. We present a new type of query based on text paragraphs.
The query execution were controled by its type and by preliminary similarities
discovered during the searches. 
In Section~\ref{text_alignment} we describe our approach for the text alignment
(pairwise comparison) subtask. We briefly introduce our system,
and then we discuss the feature types, which are usable for pairwise comparison,including the evaluation of their feasibility for this purpose. We then describe
the global (corpus-wide) optimizations used, and finally we discuss
the results achieved and further development.

\input{simon-source_retrieval}
\input{yenya-text_alignment}


\section{Conclusions}

Unfortunately the ChatNoir search engine does not support phrasal search, therefore it
is possible that evaluated results may be quite distorted in this manner.

In the text alignment subtask, we have achieved a significant improvement
with respect to our system from PAN 2012. Further development in this
area is still possible. For a real-world system, however, a completely
different set of parameters and heuristics needs to be used, as a result
of plagdet score together with the structure of the competition corpus
being too different from the real world.

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