An Approach to Model Checking of Multi-agent Data Analysis

The paper presents an approach to verification of a multi-agent data analysis algorithm. We base correct simulation of the multi-agent system by a finite integer model. For verification we use model checking tool SPIN. Protocols of agents are written in Promela language and properties of the multi-agent data analysis system are expressed in logic LTL. We run several experiments with SPIN and the model.Comment: In Proceedings MOD* 2014, arXiv:1411.345

Ontologies and Information Extraction

This report argues that, even in the simplest cases, IE is an ontology-driven process. It is not a mere text filtering method based on simple pattern matching and keywords, because the extracted pieces of texts are interpreted with respect to a predefined partial domain model. This report shows that depending on the nature and the depth of the interpretation to be done for extracting the information, more or less knowledge must be involved. This report is mainly illustrated in biology, a domain in which there are critical needs for content-based exploration of the scientific literature and which becomes a major application domain for IE

A multi-INT semantic reasoning framework for intelligence analysis support

Lockheed Martin Corp. has funded research to generate a framework and methodology for developing semantic reasoning applications to support the discipline oflntelligence Analysis. This chapter outlines that framework, discusses how it may be used to advance the information sharing and integrated analytic needs of the Intelligence Community, and suggests a system I software architecture for such applications

Towards the ontology-based approach for factual information matching

Factual information is information based on facts or relating to facts. The reliability of automatically extracted facts is the main problem of processing factual information. The fact retrieval system remains one of the most effective tools for identifying the information for decision-making. In this work, we explore how can natural language processing methods and problem domain ontology help to check contradictions and mismatches in facts automatically