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 \section{Source Retrieval}
+The source retrieval is a subtask in a plagiarism detection process during
+which only a relatively small subset of documents are retrieved from the
+large corpus. Those candidate documents are usually further compared in detail with the
+suspicious document. In the PAN 2013 source retrieval subtask the main goal was to
+identified web pages which have been used as a source of plagiarism for creation of the 
+test corpus. 
+The test corpus contained XX documents each discussing one and only one theme.
+Those documents were created intentionally by
+ semiprofessional writers, thus they feature nearly realistic plagiarism cases. 
+ Such conditions are similar to a realistic plagiarism detection scenario, such as for
+state of the art commercial plagiarism detection systems or the anti-plagiarism service developed on and
+utilized at the Masaryk University. The main difference between real-world corpus 
+of suspicious documents such as for example corpus created from theses stored in Information System of Masaryk University
+and the corpus of suspicious documents used during the PAN 2013 competition is that in the PAN
+corpus each document contains plagiarism passages. Therefore we can deepen the search during the process
+in certain parts of the document where no similar passage has yet been found. This is the main
+idea of improving recall of detected plagiarism in a suspicious document.
+
+
+\begin{figure}
+  \centering
+  \includegraphics[width=1.00\textwidth]{img/source_retrieval_process.pdf}
+  \caption{Source retrieval process.}
+  \label{fig:source_retr_process}
+\end{figure}
+
+An online plagiarism detection can be viewed as a reverse engineering task where 
+we need to find original documents from which the plagiarized document was created.
+During the process the plagiarist locates original documents with the use of a search engine.
+The user decides what query the search engine to ask and which of the results from the result page to use.
+In real-world scenario the corpus is the whole Web and the search engine can be a contemporary commercial search engine
+which scales to the size of the Web. This methodology is based on the fact that we do not
+possess enough resources to download and effectively process the whole corpus.
+In the case of PAN 2013 competition the corpus
+of source documents is the ClueWeb~\footnote{\url{http://lemurproject.org/clueweb09.php/}} corpus. 
+As a document retrieval tool for the competition we utilized the ChatNoir~\cite{chatnoir} search engine which indexes the English
+subset of the ClueWeb.   
+The reverse engineering decision process reside in creation of suitable queries on the basis of the suspicious document
+and in decision what to actually download and what to report as a plagiarism case from the search results.
+
+These first two stages can be viewed in figure~\ref{fig:source_retr_process} as Querying and Selecting. Selected results 
+from the search engine are forthwith textually aligned with the suspicious document (see section~\ref{text_alignment} for more details).
+This is the last decision phase -- what to report.
+If there is any continuous passage of reused text detected, the result document is reported
+ and the continuous passages in the suspicious document are marked as 'discovered' and no further processing
+of those parts is made. 
+ 
+\subsection{Querying}
+Querying means to effectively utilize the search engine in order to retrieve as many relevant
+documents as possible with the minimum amount of queries. We consider the resulting document relevant 
+if it shares some of text characteristics with the suspicious document.  
+
+We used 3 different types of queries~\footnote{We used similar three-way based methodology in PAN 2012 
+Candidate Document Retrieval subtask. However this time we completely replaced the headers based queries
+with paragraph based queries, since the headers based queries did not pay off in the overall process.}:
+i) keywords based queries, ii) intrinsic plagiarism
+based queries, and iii) paragraph based queries. Three main properties distinguish each type of query: i) Positional; ii) Phrasal; iii) Deterministic.
+Positional queries carry extra information about a textual interval in the suspicious document which the query represents.
+A phrasal query aims for retrieval of documents containing the same small piece of a text. They are usually created from closely coupled words. 
+Deterministic queries for specific suspicious document are always the same no matter how many times we run the software. 
+On the contrary the software can create in two runs potentially different nondeterministic queries.
+
+\subsubsection{Keywords Based Queries}
+
+\subsubsection{Intrinsic Plagiarism Based Queries}
+\subsubsection{Paragraph Based Queries}
+\subsection{Search Control}
+
+
+\subsection{Result Selection}
+\subsection{Snippet Control}
+
+
+ 
+
+
+