Benchmarking Text Understanding Systems to Human Performance: An Exploration.
Abstract
This report explores the use of natural language in intelligent computer systems specifically with regard to text understanding systems. The goal of the research was to benchmark selected text understanding systems to human performance in reading comprehension. To this end a reading comprehension test was compiled which included the texts and questions from six intelligent computer systems. This test along with a criterion reading measure was administered to the subjects in the study. The computer systems' performances were then benchmarked to a scale of human performance on reading comprehension as part of the development of the Artificial Intelligence Measurement System (AIMS).
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 1990
- Accession Number
- ADA233306
Entities
People
- Eva L. Baker
- Frances A. Butler
- Howard Herl
- Patricia Mutch
- Tine Falk
- Younghee Jang
Organizations
- University of California, Los Angeles