Ranking MEDLINE documents

Evaluating Relevance Ranking Strategies for MEDLINE Retrieval

J Am Med Inform Assoc. 2009;16:32–36. DOI 10.1197/jamia.M2935.

Ranked Set Search in Medline Documents

Information needs like searching scientific literature that involve high recall rates are difficult to satisfy with ad hoc keyword search. We propose to state queries implicitly by the specification of a set of query documents. The result of such a query is a set of answer documents that are ranked within the answer set. We describe efficient techniques to process such queries. Preliminary expe...

Querying and ranking XML documents

A Document Clustering and Ranking System for Exploring MEDLINE Citations

Design: A text mining system framework for automatic document clustering and ranking organized MEDLINE citations following simple PubMed queries. The system grouped the retrieved citations, ranked the citations in each cluster, and generated a set of keywords and MeSH terms to describe the common theme of each cluster. Measurements: Several possible ranking functions were compared, including ci...

Finding Themes in Medline Documents: Probabilistic Similarity Search

Large on-line document databases, such as Medline, pose a major challenge of retrieving the few documents most relevant to the user’s needs, while minimizing the return rate of nonrelevant documents. Retrieval of documents similar to a userprovided example document is a promising query paradigm towards meeting this goal. We present a new theme-based probabilistic approach for finding documents ...