Date: Thursday, 21-Nov-96 23:25:39 GMT Server: NCSA/1.3 MIME-version: 1.0 Content-type: text/html Last-modified: Tuesday, 19-Nov-96 20:38:32 GMT Content-length: 4611 Jody J. Daniels (daniels@cs.umass.edu)

Jody J. Daniels

Picture of me
Ph.D. Candidate

Department of Computer Science
University of Massachusetts
Amherst MA 01003-4610

Lederle Graduate Research Center
Room A249
(413) 545-1985
(413) 545-1249 fax

daniels@cs.umass.edu


Education

M.S., Computer Science, May 1993, University of Massachusetts
B.S., Applied Mathematics (Computer Science), May 1983, Carnegie Mellon University


Research

Case-Based Reasoning Laboratory

Retrieval of Passages for Information Reduction

Information Retrieval (IR) typically retrieves entire documents in response to a user's information need. However, many times a user would prefer to examine smaller portions of a document. One example of this is when building a frame-based representation of a text. The user would like to read all and only those portions of the text that are about predefined important features.

My research addresses the problem of automatically locating text about these features, where the important features are those defined for use by a case-based reasoning (CBR) system in the form of slots and fillers.

We use a small set of ``annotations'', textual segments, that have were saved when creating the original case-base to generate queries and retrieve relevant passages. Annotations are associated with the slot about which they provide information. Using a case-base of annotations for each slot we generate and pose a query to an IR system that is aimed at the retrieval of passages within a relevant document. By locating passages for display to the user, we winnow a text down to sets of several sentences, greatly reducing the time and effort expended searching through each text for important features.

This research is done in conjunction with The Center for Intelligent Information Retrieval .

For a one page abstract, see: Daniels, J.J. "Selection of Passages for Information Reduction." In Proceedings of the 13th National Conference on Artificial Intelligence (AAAI-96), 1360. Portland, OR.

Selected Papers


Other Pages


Latest Update: 7 November 1996