Accession Number : ADP007189

Title :   FGP: Using Statistics to Drive an Expert Database,

Corporate Author : YALE UNIV NEW HAVEN CT DEPT OF COMPUTER SCIENCE

Personal Author(s) : Fertig, Scott

Report Date : 1992

Pagination or Media Count : 4

Abstract : We describe the FPG machine, which uses similarity-based retrieval and simulated speculation to convert pools of data directly into quasi-expert advice. The central operation is the retrieval of a small set of records similar to a partially-instantiated new record. The system uses two statistical techniques to improve on the standard Euclidean measure for calculating distance between two records represented as a vector of features. One is a facility to automatically weight the importance of features which will add or subtract to those features' contribution to the overall distance score. The other is a means for separating the most relevant records from the rest by finding a natural break in the ordering of the records by distance from the input. We explain the role these techniques play in the overall operation of the system in the next section; the algorithms used for the calculations are described in the appendices.

Descriptors :   *ALGORITHMS, FACILITIES, INPUT, MACHINES, OPERATION, RECORDS, RECREATION, REST, STANDARDS, WEIGHT.

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE