NDLI: Textually retrieved event analysis toolset

Content Provider	IEEE Xplore Digital Library
Author	Palmer, J.
Copyright Year	2005
Description	Author affiliation: Austin Info Syst., TX (Palmer, J.)
Abstract	Of interest to the Intelligence (INTEL) community in its focus of the Global war on Terror (GWOT), is a capability to assist reasoning about events in the context of emerging patterns of behavior. An event ontology that decomposes event interactions into (actor, action, target) triplets is proposed for this purpose. Within this ontology battlespace objects (actors, targets) and their interrelationships (including actions) are formulated as graphs. The vertices represent the building blocks comprised of the individuals or capital assets necessary for war-fighting. The links or edges represent relationships between the coupled nodes that identify a specific type of association. Different links within a graph may represent different types of associations2. The increasing importance of human intelligence (HUMINT) and open source intelligence (OSINT) in combating asymmetric threats requires a capability to extract and reason about events described in free text. Attribute-based entity correlation - Level I Data Fusion (Hall and Llinas, 2001) - and inexact pattern matching techniques (e.g., subgraph isomorphism) may be sufficient to reason about the actor and target components of an event interaction triplet. Processing event description extracted from free (unstructured) text, however, requires semantic normalization and correlation to discern commonality among reported activities. A semantic comparator function is proposed to measure the similarity between the action components of extracted event triplets. The paper reviews existing work in this area such as Jiang and Conrath (Jiang and Conrath, 1997), who combine a lexical taxonomy structure (such as Princeton's WordNet) with corpus statistical information to quantify the semantic, distance between concepts. The Jiang and Conrath measure combines an edge-based approach of the edge counting scheme with a node-based approach based upon information content calculation. This paper investigates the feasibility of replacing a distributional analysis of corpus data with the Lavalette distribution (a Zipfian distribution). A prototype free text, event analysis system was developed to process simulated human intelligence information reports based on this investigation. The system was able to identify event relationships from semantic comparisons of extracted and decomposed events
Starting Page	1679
Ending Page	1685
File Size	1875737
Page Count	7
File Format	PDF
ISBN	0780393937
DOI	10.1109/MILCOM.2005.1605916
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Ontologies Humans Pattern matching Taxonomy Data analysis Virtual prototyping Information analysis Analytical models Discrete event simulation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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