TY - JOUR AU - Pan, Min AU - Zhang, Yue AU - Zhu, Qiang AU - Sun, Bo AU - He, Tingting AU - Jiang, Xingpeng PY - 2019 DA - 2019/12/12 TI - An adaptive term proximity based rocchio’s model for clinical decision support retrieval JO - BMC Medical Informatics and Decision Making SP - 251 VL - 19 IS - 9 AB - In order to better help doctors make decision in the clinical setting, research is necessary to connect electronic health record (EHR) with the biomedical literature. Pseudo Relevance Feedback (PRF) is a kind of classical query modification technique that has shown to be effective in many retrieval models and thus suitable for handling terse language and clinical jargons in EHR. Previous work has introduced a set of constraints (axioms) of traditional PRF model. However, in the feedback document, the importance degree of candidate term and the co-occurrence relationship between a candidate term and a query term. Most methods do not consider both of these factors. Intuitively, terms that have higher co-occurrence degree with a query term are more likely to be related to the query topic. SN - 1472-6947 UR - https://doi.org/10.1186/s12911-019-0986-6 DO - 10.1186/s12911-019-0986-6 ID - Pan2019 ER -