UESTC at ImageCLEF 2010 Medical Retrieval Task

This paper presents the UESTC contribution to the ImageCLEF 2010 medical retrieval task. For ad-hoc retrieval and case-based retrieval, we only use text information, and propose a phrase-based approach. Phrases, subphrases and individual words are used with vector space model (VSM) for ranking. Phrases and subphrases are extracted with the help of MetaMap, and all extracted phrasal terms are corresponding to concepts in UMLS. Two term weighting methods are proposed, one is to weight terms with their idfs, and the other is adapted to assign lower weights to phrasal terms. We also propose a query expansion method which can extract more phrases for query by relaxing the restrictions on phrase extraction. For modality classification, we use three global texture features with SVM and Ada-boost.MH respectively.

• Type: Conference
• Year: 2010
• Where: CLEF
• Authors: Hong Wu, Changjun Hu, Sikun Chen
• Keywords: Ad-hoc Retrieval, CLEF 2010, Information Technology, Medical Retrieval Task, Phrasal Terms