Advanced Semantic Technologies

KBSI is an industry leader in the development of semantic technologies, assisting government and commercial organizations to more effectively leverage their information and data for their business operations. The growth and availability of data, both externally and internally, and the current systems for warehousing this data have hindered the ability to effectively utilize it in decision-making and planning.  Semantic technologies provide an intelligent platform for analyzing and utilizing data, delivering new insights to organizations and improving their products and services.

KBSI has extensive experience in the creation and application of advanced and innovative semantic technologies that are being applied in a wide variety of organizations today. These technologies have become central to a broad range of our research and development initiatives, including work with the DoD, NASA, DOE and the Department of Homeland Security in areas such as medical data mining, threat detection, computer network security, discovery of disease outbreaks, cash reserves management and financial fraud detection, decision making and training, target decoy recognition, the redesigning of multi-agent systems, and business intelligence.

 

 

JackalFish®

Use the Jackalfish® tool to perform targeted searches of disparate data sources using either keywords, extracted phrases or paragraphs from target documents, common concepts, and/or defined ontology relationships. The tool's ontology-assisted text mining and natural language processing methods provide knowledge extraction from structured and unstructured text sources.

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Ontology Driven Integration Framework (ODIF)

KBSI designed and developed technology that automates the sharing and integration of information among different organizations. The development of a common ontology for integrating diverse data sources, combined with knowledge extraction techniques and ontology analysis methods, will allow users to extract knowledge from distributed, unstructured text sources and share knowledge among large-scale project teams.

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Framework for Adaptive Modeling and Ontology-driven Simulation (FAMOS™)

KBSI built a system for the development and execution of distributed military simulation applications. The FAMOS™ technology reduces the time and effort needed for developing and deploying distributed simulation applications and lays the groundwork for knowledge sharing, communication, and semantic integration among modeling and simulation applications.

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Toolkit for Agent-based Knowledge Extraction (TAKE™)

KBSI applied a hybrid approach that combines ontology engineering methods with cutting-edge knowledge discovery techniques to extract, analyze, and map ontologies from distributed and disparate knowledge and data sources. The TAKE™ technology enables the rapid and cost effective analysis, redesign, integration and/or reengineering of complex systems.

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Adaptive Toolkit for the Discovery of Threats (ATDT)

KBSI developed a toolkit that integrates intelligent knowledge discovery techniques, advanced data mining technologies, and knowledge-based methods for automated threat detection. ATDT is an agent-based decision support system that mines data (news feeds, web databases, traffic reports, radio intercepts, human intelligence, etc.) to extract meaningful knowledge or "indicators" of emerging threats.

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Information-Fusion based Indication & Warning Assessment and Recognition System (IIWARS)

KBSI developed a system that, using text mining technologies and information fusion, improves the DoD's terrorist threat assessment capabilities. IIWARS uses advanced text and data mining methods to mine data from multiple, distributed text sources (news feeds, web databases, traffic reports, radio intercepts, human intelligence) and extract multiple features and "indicators" of an emerging or actual threat. These indicators are then fused into a threat model which can be compared to hypothesized threat Course Of Action (COA) templates.

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Data Display Translation Framework (DDTF)

KBSI customized an advanced, component-based Data Display Markup Language (DDML), an XML-based neutral format also developed by KBSI, as the inter-lingua for translating the data display languages supported by different vendors.

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Faraday Chromate

KBSI analyzed Electro Impedance Spectroscopy (EIS) data with the objective of studying the effectiveness and life of particular coatings in accelerated corrosion environments. 

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Framework for Interoperability of Executable Architectures (FIEA)

KBSI is developing a language, tool framework, and methodology that will enable users to share data among the many vendor specific tools and applications they use. 

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Hybrid Decision Wizard (HDWizard™)

KBSI developed, built, and validated a hybrid decision support toolkit that utilizes a combination of common sense reasoning, domain knowledge based reasoning, and soft computing techniques to support intelligent decision making. The HDWizard™ technology is an agent-based decision support system that facilitates the automated generation of information from disparate and distributed data to support user-defined decision support goals.

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Hybrid Framework for Information Visualization Enablers (HI-FIVE)

KBSI designed a novel, model-based, “no-programming required” approach to information visualization. HI-FIVE provides an extendible framework for rapidly developing, configuring, and managing data displays, enabling the understanding of “system of systems” data.  

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Knowledge Discovery Wizard (KDWIZARD)

KBSI designed, developed, and validated an adaptive framework for knowledge discovery. This framework provides mechanisms for generating knowledge-discovery applications beginning with end-user specifications of decision objectives and sets of data sources, provides users with a larger and more focused selection of decision alternatives.

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XML/IDEF3-based Training

KBSI defined a neutral format for capturing, organizing, and sharing process-related knowledge that is based on the Integrated Definition family of methods and the eXtended Markup Language (XML). Using this standard, KBSI developed an advanced authoring tool-kit for situation-based, process-centric computer-based training systems.

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Adaptive Toolkit for Pattern Discovery (ATPD)

KBSI combined new machine learning techniques with advanced rule based methods for automated data utilization pattern discovery. The ATPD technology allows users to monitor information use, discover use patterns, and develop ontology models that capture data relations and patterns.

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