# Document Retrieval System for Biomedical Question Answering
## 3 Results  
### Document Retrieval Component Evaluation  
In general, we obtained the following results based on the test results. * Dirichlet similarity method with expanding query with MESH terms produces the best performance for 100 questions and MAP@20. * Expanded query with noun/noun phrases increases the performance. * Expanded query with mesh terms increases the performance. * Expanded query with stemming terms has a better performance than expanded query with UMLS concept. \begin{table}
\begin{tabular}{l c c c c} \hline \hline  & **MAP@20** & **Precision** & **Recall** & **F-Score** \\ \hline Lucene Step & 0.215067938 & 0.1675 & 0.378670918 & 0.207030739 \\ Feedback Step & 0.205558147 & 0.1605 & 0.338886485 & 0.197606624 \\ Stemming Step & 0.193653656 & 0.145 & 0.334537667 & 0.182408129 \\ Re-rank Step & 0.127871192 & 0.1175 & 0.258922228 & 0.144890457 \\ \hline \multicolumn{5}{c}{Expanding with Nouns + MESH terms} \\ \hline Feedback Step & 0.212765534 & 0.1615 & 0.352054511 & 0.199110331 \\ Lucene Step & 0.211291773 & 0.1555 & 0.347947469 & 0.193621451 \\ Stemming Step & 0.193653656 & 0.145 & 0.334537667 & 0.182408129 \\ Re-rank Step & 0.128392227 & 0.109 & 0.244808347 & 0.13491335 \\ \hline \multicolumn{5}{c}{Expanding with UMLS Concepts + MESH terms} \\ \hline Stemming Step & 0.193653656 & 0.145 & 0.334537667 & 0.182408129 \\ Feedback Step & 0.150857459 & 0.1315 & 0.272468562 & 0.15882982 \\ Lucene Step & 0.131512942 & 0.1125 & 0.239383041 & 0.136570818 \\ Re-rank Step & 0.063413178 & 0.066 & 0.172869037 & 0.083156168 \\ \hline \hline \end{tabular}
\end{table} 
Table 13: Performance of the Bayesian Smoothing with Dirichlet Priors Model. \begin{table}
\begin{tabular}{l c c c c} \hline \hline
**System** & **Mean Precision** & **Recall** & **F-Measure** & **MAP** & **GMAP** \\ \hline RYGH-1 & 0.2889 & 0.6122 & 0.2999 & 0.5624 & 0.0992 \\ RYGH-4 & 0.2774 & 0.6177 & 0.2943 & 0.5620 & 0.1286 \\ RYGH-3 & 0.2765 & 0.6162 & 0.2937 & 0.5538 & 0.1267 \\ \hline \hline \end{tabular}
\end{table} 
Table 14: Performance of the Jelinek–Mercer Smoothing Model. \begin{table}
\begin{tabular}{l c c c} \hline \hline  & **Expanding with MESH Terms** & & \\ \hline Feedback Step & 0.194099982 & 0.153 & 0.320348831 & 0.186614216 \\ Lucene Step & 0.190455137 & 0.146 & 0.330585442 & 0.180809385 \\ Stemming Step & 0.188270263 & 0.139 & 0.318224318 & 0.174046006 \\ Re-rank Step & 0.134464863 & 0.115 & 0.257101004 & 0.141889457 \\ \hline \multicolumn{5}{c}{Expanding with Nouns + MESH terms} \\ \hline Feedback Step & 0.194028485 & 0.1505 & 0.311523233 & 0.183403315 \\ Stemming Step & 0.188270263 & 0.139 & 0.318224318 & 0.174046006 \\ Lucene Step & 0.186934951 & 0.1435 & 0.328282514 & 0.17944826 \\ Re-rank Step & 0.148731105 & 0.124 & 0.28247245 & 0.153743885 \\ \hline \multicolumn{5}{c}{Expanding with UMLS Concepts + MESH terms} \\ \hline Stemming Step & 0.188270263 & 0.139 & 0.318224318 & 0.174046006 \\ Feedback Step & 0.137930359 & 0.1195 & 0.253599299 & 0.144541146 \\ Re-rank Step & 0.094030546 & 0.0815 & 0.196744006 & 0.102584254 \\ Lucene Step & 0.092639625 & 0.081 & 0.174941453 & 0.097931787 \\ \hline \hline \end{tabular}
\end{table} 
Table 15: MAP score of document retrieval system.