DATA DRIVEN ACTIVITY BASED INTELLIGENCE
IFT’s Data Driven Activity Based Intelligence (DDABI) tool collects real-time streaming data from multiple public data sources. DDABI then interprets and extracts interactions, events, and activities. Ultimately, performing Multi-Intelligence Knowledge fusion and Reasoning, to discover relevant patterns, determine anomalies, and identify latent risks.
Unlike currently available tools on the market, DDABI’s output is not just a collection of postings filtered by keywords. DDABI also provides in-depth insights gained through advanced semantic analysis. While DDABI is intended for analysts and decision makers within the military Intelligence community, it can also be extended to the commercial sector.
METHOD: Activity Based Intelligence
KEYWORDS: Knowledge Graph, Natural Language Processing, Unstructured Data Extraction and Fusion, Pattern Analysis, Anomaly Detection
TECHNICAL SPECS: Python, JAVA, Spring Boot
RESEARCH: Anomaly Detection of Unstructured Big Data via Semantic Analysis and Dynamic Knowledge Graph Construction