+\STATE $I \leftarrow \emptyset; I \in \mathbb{N}^2$
+\STATE $W \leftarrow \emptyset$
+
+\FORALL{$q \in (Q_{KW} \cup Q_{Intrinsic} \cup Q_{Headers}) $}
+ \IF{$position(q)$ do not intersects with any interval $ \vec{i} \in I$}
+ \STATE $W \leftarrow execute(q)$
+ \FORALL{$w \in W$}
+ \STATE $I_{sub} \leftarrow get\_similarities(w, d)$ %\COMMENT{output is set of intervals similarities $[d_{start},d_{end}]$}
+ \STATE $I \leftarrow I \cup I_{sub}$
+ \IF{$I_{sub} \neq \emptyset$}
+ \STATE $W_{plag} \leftarrow W_{plag} \cup \{w\}$
+ \ENDIF
+ \ENDFOR
+ \ENDIF
+\ENDFOR
+\RETURN $W_{plag}$
+
+\end{algorithmic}
+\end{algorithm}
+
+\subsection{Queries comparison}~\label{comparison}
+During the test phase there were extracted 133 keywords based queries, 165 intrinsic plagiarism
+based queries and 331 headers based queries from the test corpus in total. Table~\ref{querycount} compares
+results according to query types.
+\begin{center}
+\begin{table}[h]
+\begin{center}
+\begin{tabular}{|c|c|c|c|}
+\hline
+{\bf Query type} & {\bf Extracted}& {\bf Omitted} & {\bf Similarities portion }\\ \hline \hline
+KW & 4.16 & N/A & 72.5\% \\ \hline
+Intrinsic & 5.16 & 2.35 & 24.3\% \\ \hline
+Headers & 10.34 & 4.75 & 3.2\% \\ \hline
+\end{tabular}\\
+\end{center}
+\vspace{0.3 cm}
+\caption{\footnotesize Queries type comparison.}
+\label{querycount}
+\end{table}
+\end{center}
+The second and the third column
+represents the mean of the query count and the omitted query count per document. The fourth
+column shows total portion of similarities found, taking into account the number of similarities regardless of interval sizes.
+ We can see that nearly half of the prepared queries were
+omitted due to the fact, that there had been found a similarity covering their document position.
+We can also see that there were detected about 5 cases
+of potential plagiarism on average, by means of used AWFC intrinsic plagiarism detection method.
+Table~\ref{querycount} also shows keyword based queries as the most successful and
+headers based queries as the least successful. Despite the fact, that they were greatest
+in number they ended with only more than a 3\% of total similarities found. Nevertheless, please
+note that the headers based queries were executed as the last, thus they were used only for
+finding undiscovered potential similarities. In order to really compare the query type performance, we
+would need to execute and evaluate them separately.
+
+To conclude this section we can say, that all types of queries were more or less successful. The headers based
+were executed last and in the process they were the least successful. The interesting
+ finding is the fact, that we can even greatly lower the number of executed queries.
+By omitting all of headers based queries we could lover the total number of executed queries by 45\% with only
+3.2\% of recall lost.
+%\begin{center}
+
+
+
+\begin{table}[h]
+\begin{center}
+{ \scriptsize
+\begin{tabular}{l c c c c c c c c c c c }
+\hline
+& \multicolumn{2}{c}{\strut \bf Total workload} & \multicolumn{2}{c}{\bf Time to 1st Result}&\multirow{2}{*}{\parbox{0.6cm}{\bf No \\ result}} &
+\multicolumn{2}{c}{\bf Reported Srcs.} & \multicolumn{2}{c}{\bf Downloaded Srcs.} &
+ \multicolumn{2}{c}{\bf Retrieved Srcs.} \\
+
+{\bf Team \strut}&{\bf Queries}&{\bf Downloads}&{\bf Queries}&{\bf Downloads}
+& & {\bf Prec.}&{\bf Recall}&{\bf Prec.}&{\bf Recall}&{\bf Prec.}&{\bf Recall}\\ \hline \hline
+
+\parbox{2,3cm}{\strut Gillam et al. \\ University of Surrey, UK \strut} & 63.44 & 527.41 & 4.47 &
+ 25.88 & {\bf 1} & 0.6266 & 0.2493 & 0.0182 & {\bf 0.5567} & 0.0182 & {\bf 0.5567} \\ %\hline
+
+\parbox{2,3cm}{\strut Jayapal \\ University of Sheffield, UK \strut}& 67.06 & 173.47 & 8.78 & 13.50 &
+ 1 & {\bf 0.6582} & {\bf 0.2775} & 0.0709 & 0.4342 & {\bf 0.0698} & 0.4342 \\ %\hline
+
+ \parbox{2,3cm}{\strut Kong Leilei \\ Heilongjiang Institute of Technology,\\ China \strut } & 551.06 &
+ 326.66 & 80.59 & 27.47 & 2 & 0.5720 & 0.2351 & 0.0178 & 0.3742 & 0.0141 & 0.3788 \\ %\hline
+
+\parbox{2,3cm}{\strut Palkovskii et al. \\ Zhytomyr State University, Ukraine \strut} & 63.13 &
+1026.72 & 27.28 & 318.94 & 6 & 0.4349 & 0.1203 & 0.0025 & 0.2133 & 0.0024 & 0.2133 \\ %\hline
+
+\parbox{2,3cm}{\strut \bf our approach \strut }& {\bf 12.56} & {\bf 95.41} & {\bf 1.53} & {\bf 6.28} & 2 & 0.5177 & 0.2087 & {\bf 0.0813} &
+0.3513 & 0.0094 & 0.4519 \\ \hline
+\end{tabular}\\}
+\end{center}
+\vspace{0.3 cm}
+\caption{\footnotesize PAN 2012 candidate document retrieval results.}
+\label{candidateDocsResults}
+\end{table}
+%\end{center}
+
+Table~\ref{candidateDocsResults} shows results of PAN 2012 candidate document retrieval
+task as averages over the all 32 documents from the test corpus. Our approach led
+to obtain decent retrieval performance with the minimal total workload and minimal time to 1st result.
+Also the 80\% word match threshold in Web snippet appears to be suitable, since we
+also achieved the highest precision among downloaded sources.
+
+
+
+