TY - JOUR
T1 - Concept-based medical document retrieval
T2 - 2013 Cross Language Evaluation Forum Conference, CLEF 2013
AU - Zhong, Xiaoshi
AU - Xia, Yunqing
AU - Xie, Zhongda
AU - Na, Sen
AU - Hu, Qinan
AU - Huang, Yaohai
PY - 2013
Y1 - 2013
N2 - We describe our participation in the task 3 of ShARe/CLEF eHealth Lab 2013: information retrieval to address questions patient may have when reading clinical reports. In our experiments, we focus mainly on two levels of analysis, namely query analysis and document analysis, to disclose the relevance between query and documents. In terms of query analysis, we first observe each medical-oriented query to find its identical or related UMLS concepts derived from the query, which may help to induce relevant results that refer to the same thing but are represented in other surface forms. In such manner, we extend the query based on the medical concepts so as to achieve a bigger coverage. In terms of document analysis, we leverage different scores (e.g., relevance score, PageRank score, HITS score and layout score) as feature to re-rank the documents of search results. With those two levels of analysis, we implement a concept-based method and a topic-based method to accomplish the task of medical document retrieval. Experiments indicate that the proposed method is effective.
AB - We describe our participation in the task 3 of ShARe/CLEF eHealth Lab 2013: information retrieval to address questions patient may have when reading clinical reports. In our experiments, we focus mainly on two levels of analysis, namely query analysis and document analysis, to disclose the relevance between query and documents. In terms of query analysis, we first observe each medical-oriented query to find its identical or related UMLS concepts derived from the query, which may help to induce relevant results that refer to the same thing but are represented in other surface forms. In such manner, we extend the query based on the medical concepts so as to achieve a bigger coverage. In terms of document analysis, we leverage different scores (e.g., relevance score, PageRank score, HITS score and layout score) as feature to re-rank the documents of search results. With those two levels of analysis, we implement a concept-based method and a topic-based method to accomplish the task of medical document retrieval. Experiments indicate that the proposed method is effective.
KW - Concept
KW - Document ranking
KW - Medical document retrieval
KW - Query analysis
KW - Topic
UR - http://www.scopus.com/inward/record.url?scp=84922021335&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84922021335
SN - 1613-0073
VL - 1179
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
Y2 - 23 September 2013 through 26 September 2013
ER -