Teacher:In this task, you are given a passage which has a question and the context. You have to generate an answer to the question based on the information present in the context.
Teacher: Now, understand the problem? Solve this instance: Context: Most of the information in Electronic Health Records (EHRs) is represented in free textual form. Practitioners searching EHRs need to phrase their queries carefully, as the record might use synonyms or other related words. In this paper we show that an automatic query expansion method based on the Unified Medicine Language System (UMLS) Metathesaurus improves the results of a robust baseline when searching EHRs.', 'The method uses a graph representation of the lexical units, concepts and relations in the UMLS Metathesaurus. It is based on random walks over the graph, which start on the query terms. Random walks are a well-studied discipline in both Web and Knowledge Base datasets.', 'Our experiments over the TREC Medical Record track show improvements in both the 2011 and 2012 datasets over a strong baseline.\Question: Does improving search over Electronic Health Records using UMLS-based query expansion through random walk?
Student:
Our analysis shows that the success of our method is due to the automatic expansion of the query with extra terms, even when they are not directly related in the UMLS Metathesaurus. The terms added in the expansion go beyond simple synonyms, and also add other kinds of topically related terms.