Changeset - 12c3faed77f6
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Arjen de Vries (arjen) - 11 years ago 2014-06-12 04:01:07
arjen.de.vries@cwi.nl
minor - remove table ref not necessary
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mypaper-final.tex
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@@ -543,98 +543,98 @@ If we look at the recall performances for the raw corpus,   filtering documents
 
%	                 &all-part $-$ cano-part &4.2  &26.9   &15.8          &0.2    &0.7    &6.7           &72.2   &8%7.6 &75 \\
 
%	                 &all-part $-$ all     	&3    &5.4     &10.7           &2.1  &2.9    &11              &18.2   &%11.3    &9 \\
 
%	                 
 
%	                 \hline
 
%\multirow{4}{*}{total} 	&cano-part $-$ cano   	&10.9   &15.5   &12.4         &11.9  &21.3   &14.4          &0 %    &0       &0\\
 
%			&all $-$ cano         	&13.8   &30.6   &16.9         &9.1  &18.9   &10.2          &63.6  &61.8%    &57.5 \\
 
%                        &all-part $-$ cano-part	&7.2   &24.8   &15.9          &0.1    &0.7    &6.8           &8%2.2  &89.1    &71.3\\
 
%                        &all-part $-$ all     	&4.3   &9.7    &11.4           &3.0  &3.1   &11.0          &18.9  &27.3%    &13.8\\	                 
 
%	                 
 
%                                  	                 
 
%\hline
 
%\end{tabular}
 
%\end{center}
 
%\label{tab:source-delta2}
 
%\end{table*}
 
 
 
 \begin{table*}
 
\caption{Breakdown of recall performances by document source category}
 
\begin{center}\begin{tabular}{l*{9}{c}r}
 
 && \multicolumn{3}{ c| }{All entities}  & \multicolumn{3}{ c| }{Wikipedia} &\multicolumn{3}{ c| }{Twitter} \\ 
 
 & &others&news&social & others&news&social &  others&news&social \\
 
\hline
 
 
 
\multirow{4}{*}{Vital} &cano                 &82.2& 65.6& 70.9& 90.9&  80.1& 76.8&   8.1&  6.3&  30.5\\
 
&cano part & 90.4& 80.6& 83.1& 100.0& 98.7& 90.9&   8.1&  6.3&  30.5\\
 
&all  & 94.8& 85.4& 83.1& 96.4&  95.9& 85.2&   81.1& 42.2& 68.8\\
 
&all part &100& 99.2& 95.9& 100.0&  99.2& 96.0&   100&  99.3& 94.9\\
 
\hline
 
	                 
 
\multirow{4}{*}{Relevant} &cano & 84.2& 53.4& 55.6& 88.4& 75.6& 63.2& 10.6& 2.2& 6.0\\
 
&cano part &94.7& 68.5& 67.8& 99.6& 97.3& 77.3& 10.6& 2.2& 6.0\\
 
&all & 95.8& 90.1& 72.9& 97.6& 95.1& 73.1& 65.2& 78.4& 72.0\\
 
&all part &98.8& 95.5& 83.7& 99.7& 98.0& 84.1& 83.3& 89.7& 81.0\\
 
	                 
 
	                 \hline
 
\multirow{4}{*}{total} 	&cano    &   81.1& 56.5& 58.2& 87.7& 76.4& 65.7& 9.8& 3.6& 13.5\\
 
&cano part &92.0& 72.0& 70.6& 99.6& 97.7& 80.1& 9.8& 3.6& 13.5\\
 
&all & 94.8& 87.1& 75.2& 96.8& 95.3& 75.8& 73.5& 65.4& 71.1\\
 
&all part & 99.2& 96.8& 86.6& 99.8& 98.4& 86.8& 92.4& 92.7& 84.9\\
 
	                 
 
\hline
 
\end{tabular}
 
\end{center}
 
\label{tab:source-delta}
 
\end{table*}
 
    
 
 
The break down of the raw corpus by document source category is presented in Table
 
\ref{tab:source-delta}.  
 
%The break down of the raw corpus by document source category is presented in Table
 
%\ref{tab:source-delta}.  
 
 
 
 
 
 
 
 
 
 \subsection{ Relevance Rating: vital and relevant}
 
 
 
When comparing recall for vital and relevant, we observe that
 
canonical names are more effective for vital than for relevant
 
entities, in particular for the Wikipedia entities. 
 
%For example, the recall for news is 80.1 and for social is 76, while the corresponding recall in relevant is 75.6 and 63.2 respectively.
 
We conclude that the most relevant documents mention the
 
entities by their common name variants.
 
%  \subsection{Difference by document categories}
 
%  
 
 
 
%  Generally, there is greater variation in relevant rank than in vital. This is specially true in most of the Delta's for Wikipedia. This  maybe be explained by news items referring to  vital documents by a some standard name than documents that are relevant. Twitter entities show greater deltas than Wikipedia entities in both vital and relevant. The greater variation can be explained by the fact that the canonical name of Twitter entities retrieves very few documents. The deltas that involve canonical names of Twitter entities, thus, show greater deltas.  
 
%  
 
 
% If we look in recall performances, In Wikipedia entities, the order seems to be others, news and social. This means that others achieve a higher recall than news than social.  However, in Twitter entities, it does not show such a strict pattern. In all, entities also, we also see almost the same pattern of other, news and social. 
 
 
 
 
  
 
\subsection{Recall across document categories: others, news and social}
 
The recall for Wikipedia entities in Table \ref{tab:name} ranged from
 
61.8\% (canonicals) to 77.9\% (name-variants).  Table
 
\ref{tab:source-delta} shows how recall is distributed across document
 
categories. For Wikipedia entities, across all entity profiles, others
 
have a higher recall followed by news, and then by social.  While the
 
recall for news ranges from 76.4\% to 98.4\%, the recall for social
 
documents ranges from 65.7\% to 86.8\%. In Twitter entities, however,
 
the pattern is different. In canonicals (and their partials), social
 
documents achieve higher recall than news.
 
%This indicates that social documents refer to Twitter entities by their canonical names (user names) more than news do. In name- variant partial, news achieve better results than social. The difference in recall between canonicals and name-variants show that news do not refer to Twitter entities by their user names, they refer to them by their display names.
 
Overall, across all entities types and all entity profiles, documents
 
in the others category achieve a higher recall than news, and news documents, in turn, achieve higher recall than social documents. 
 
 
% This suggests that social documents are the hardest  to retrieve.  This  makes sense since social posts such as tweets and blogs are short and are more likely to point to other resources, or use short informal names.
 
 
 
%%NOTE TABLE REMOVED:\\\\
 
%
 
%We computed four percentage increases in recall (deltas)  between the
 
%different entity profiles (Table \ref{tab:source-delta2}). The first
 
%delta is the recall percentage between canonical partial  and
 
%canonical. The second  is  between name= variant and canonical. The
 
%third is the difference between name-variant partial  and canonical
 
%partial and the fourth between name-variant partial and
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