-Such a change may point out plagiarized passage which is intrinsically bound up with the text. \r
-We implemented vocabulary richness method which computes average word frequency class value for \r
-a given text part. The method is described in~\cite{awfc}. The problem is that generally methods\r
-based on the vocabulary statistics work better for longer texts. According to authors this method\r
-scales well for shorter texts than other text style detection methods. \r
-Still the usage is in our case limited by relatively short texts. It is also difficult to determine\r
-what parts of text to compare. Therefore we used sliding window concept for text chunking with the \r
-same settings as described in~\cite{suchomel_kas_12}.\r
+%Such a change may point out plagiarized passage which is intrinsically bound up with the text. \r
+%We implemented vocabulary richness method which computes average word frequency class value for \r
+%a given text part. The method is described in~\cite{awfc}.\r
+For this purpose we implemented vocabulary richness method~\cite{awfc} together with\r
+sliding windows concept for text chunking as described in~\cite{suchomel_kas_12}.\r
+%The problem is that generally methods based on the vocabulary statistics work better for longer texts.\r
+%According to authors this method scales well for shorter texts than other text style detection methods. \r
+%The usage of this method is in our case limited by relatively short texts.\r
+%It is also difficult to determine\r
+%what parts of text to compare. Therefore we used sliding window concept for text chunking with the \r
+%same settings as described in~\cite{suchomel_kas_12}.\r