CERTAIN: Certainty Enrichment via Relational and Temporal Analytical Indexing of Networks
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AbstractEfficient and accurate indexing is fundamental to the Big Data enterprise, but traditional indexing techniques are often foiled by noise and missing information. Aptima proposes Phase II of CERTAIN (Certainty Enrichment via Relational and Temporal Analytical Indexing of Networks), an approach that advances several areas of large dataset indexing and applies them to the domains of cyber and financial analysis. We will extend, implement and integrate the indexing approach prototyped in Phase I that retrieves data that traditional indexers miss. Our enriched indexing approach relies on inference algorithms that extract high level features in temporal and relational datasets. Phase I focused on detecting patterns of temporal behavior by learning categories of records that share qualitatively similar characteristics. Phase II builds upon and enhances that work to now focus on the relational domain, where we will detect subnetwork primitives that highlight regions of a dataset that share similar properties. We will demonstrate how inference-enriched indexing supports query by example and improves the retrieval of relevant data by intelligently managing noisy datasets. Our research and development effort will focus on both cyber and financial datasets, but our approach will extend to other data sources that have temporal or relational components.
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