Centrality based Document Ranking
Abstract
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, Lucene1 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 re-rank 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.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 01, 2014
- Accession Number
- ADA618774
Entities
People
- Aastha Singh
- C. R. Chowdary
Organizations
- Banaras Hindu University