Academic Journal

Probabilistic Knowledge Base Validation

Bibliographic Details
Title: Probabilistic Knowledge Base Validation
Authors: Gleason, Howard T.
Source: Theses and Dissertations
Publisher Information: AFIT Scholar
Publication Year: 1995
Collection: AFTI Scholar (Air Force Institute of Technology)
Subject Terms: Bayesian statistical decision theory, Expert systems (Computer science), Computer software--Validation, Computer Sciences
Description: Our work develops a new methodology and tool for the validation of probabilistic knowledge bases throughout their lifecycle. The methodology minimizes user interaction by automatically modifying incorrect knowledge; only the occurrence of incomplete knowledge involves interaction. These gains are realized by combining and modifying techniques borrowed from rule-based and artificial neural network validation strategies. The presented methodology is demonstrated through BVAL, which is designed for a new knowledge representation, the Bayesian Knowledge Base. This knowledge representation accommodates incomplete knowledge while remaining firmly grounded in probability theory.
Document Type: text
File Description: application/pdf
Language: unknown
Relation: https://scholar.afit.edu/etd/6143; https://scholar.afit.edu/context/etd/article/7146/viewcontent/AFIT_GCS_ENG_95D_04_Gleason_H_ADA303824_Redacted.pdf
Availability: https://scholar.afit.edu/etd/6143
https://scholar.afit.edu/context/etd/article/7146/viewcontent/AFIT_GCS_ENG_95D_04_Gleason_H_ADA303824_Redacted.pdf
Accession Number: edsbas.D1B79768
Database: BASE
Description
Description not available.