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Semantic Analytics in Intelligence

Applying Semantic Association Discovery to Determine Relevance of Heterogeneous Documents
Authors: Aleman-Meza, Boanerges; Sheth, Amit P.; Paliniswami, Devanand; Eavenson, Matthew; Arpinar, I. Budak;

Semantic Analytics in Intelligence

Abstract

We describe an ontological approach for determining the relevance of documents based on the underlying concept of exploiting complex semantic relationships among real-world entities. This research builds upon semantic metadata extraction and annotation, practical domain-specific ontology creation, main-memory query processing, and the notion of semantic association. A prototype application illustrates the approach by supporting the identification of insider threats for document access. In this scenario, we describe how investigative assignments performed by intelligence analysts are captured into a context of investigation by including concepts andrelationships from the ontology. A relevance measure for documents is computed using semantic analytics techniques. Additionally, a graph-based visualization component allows exploration of potential document access beyond the ‘need to know’. We also discuss how a commercial product using Semantic Web technology, Semagix Freedom, is used for metadata extraction when designing and populating an ontology from heterogeneous sources.

Keywords

Knowledge Base, Semantic Associations, Databases and Information Systems, Bioinformatics, Data Security, OS and Networks, Social and Behavioral Sciences, Semantic Web Technology, Science and Technology Studies, RDF, Semantic Analytics, heterogeneous documents, Physical Sciences and Mathematics, Semantic Applications for Homeland Security, Semantic Ranking, Graph Traversal, Computer Engineering, Semantic Web, Ontology, Computer Sciences, Communication, Context, Life Sciences, Complex Relationships, Electrical and Computer Engineering, Knowledge Discovery, 004, Semantic Relationships, semantic analytics, Semantic Matching, Semantic Discovery, Insider Threat, Communication Technology and New Media, semantic, Ranking, Semantic Metadata, Relevance of Information

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
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