Final Report on MITRE Evaluations for the DARPA Big Mechanism Program

This report presents the evaluation approach developed for the DARPA Big Mechanism program, which aimed at developing computer systems that will read research papers, integrate the information into a computer model of cancer mechanisms, and frame new hypotheses. We employed an iterative, incremental approach to the evaluation of the three phases of the program. In Phase I, we evaluated the ability of system and human teams ability to read-with-a-model to capture mechanistic information from the biomedical literature, integrated with information from expert curated biological databases. In Phase II we evaluated the ability of systems to assemble fragments of information into a mechanistic model. The Phase III evaluation focused on the ability of systems to provide explanations of experimental observations based on models assembled (largely automatically) by the Big Mechanism process. The evaluation for each phase built on earlier evaluations and guided developers towards creating capabilities for the new phase. The report describes our approach, including innovations such as a reference set (a curated data set limited to major findings of each paper) to assess the accuracy of systems in extracting mechanistic findings in the absence of a gold standard, and a method to evaluate model-based explanations of experimental data. Results of the evaluation and supporting materials are included in the appendices.Comment: 46 pages, 8 figure

A learning approach to knowledge acquisition for intelligent interface agents

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1993.Includes bibliographical references (leaves 99-100).by Robyn Arlene Edelson Kozierok.M.S

Mitap: A case study of integrated knowledge discovery tools

The MiTAP system was developed as an experimental prototype using human language technologies for the monitoring of infectious disease outbreaks. The system provides timely, multi-lingual, global information access to analysts, medical experts and individuals involved in humanitarian assistance and relief work. Each day, thousands of articles from electronic information sources spanning multiple languages are automatically captured, translated, tagged, summarized, and presented to users in a variety of ways. Over the course of the past year and half, MiTAP has become a useful tool for real users to solve real problems. The success of MiTAP is greatly attributed to its user-focused design that accommodates the imperfect component technologies and that allows users to interact with the system in familiar ways. We will discuss the problem, the design process, and the implementation from the perspective of services provided and how these services support system capabilities that satisfy user requirements. 1