Leveraging a Common Representation for Personalized Search and Summarization in a Medical Digital Library
Houston, Texas USA
May 27, 2003 to May 31, 2003
Kathleen R. McKeown , Columbia University
Noemie Elhadad , Columbia University
Vasileios Hatzivassiloglou , Columbia University
Despite the large amount of online medical literature, it can be difficult for clinicians to find relevant information at the point of patient care. In this paper, we present techniques to personalize the results of search, making use of the online patient record as a sophisticated, pre-existing user model. Our work in PERSIVAL, a medical digital library, includes methods for re-ranking the results of search to prioritize those that better match the patient record. It also generates summaries of the re-ranked results which highlight information that is relevant to the patient under the physician?s care. We focus on the use of a common representation for the articles returned by search and the patient record which facilitates both the re-ranking and the summarization tasks.This common approach to both tasks has a strong positive effect on the ability to personalize information.
Kathleen R. McKeown, Noemie Elhadad, Vasileios Hatzivassiloglou, "Leveraging a Common Representation for Personalized Search and Summarization in a Medical Digital Library", JCDL, 2003, Digital Libraries, Joint Conference on, Digital Libraries, Joint Conference on 2003, pp. 159, doi:10.1109/JCDL.2003.1204856