Centrality based Document Ranking
نویسندگان
چکیده
In this paper, we address the problem of ranking clinical documents using centrality based approach. We model the documents to be ranked as nodes in a graph and place edges between documents based on their similarity. Given a query, we compute similarity of the query with respect to every document in the graph. Based on these similarity values, documents are ranked for a given query. Initially, Lucene is used to retrieve top fifty documents that are relevant to the query and then our proposed approach is applied on these retrieved documents to rerank them. Experimental results show that our approach did not perform well as the documents retrieved by Lucene are not among the top 50 documents in the Gold Standard.
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