Scoring Analysis via Data Integration and Information Extraction (SADIIE) Navy SBIR FY2014.1 Sol No.: Navy SBIR FY2014.1 Topic No.: N141-037 Topic Title: Scoring Analysis via Data Integration and Information Extraction (SADIIE) Proposal No.: N141-037-0903 Firm: Applied Technical Systems Inc. 3505 NW Anderson Hill Rd Suite 200 Silverdale, Washington 98383 Contact: Doug West Phone: (757) 483-5959 Web Site: www.atsid.com Abstract: Applied Technical Systems, Inc. (ATS) proposes to leverage its expertise with maintenance and logistics support of Naval systems and its experience in developing data-rich software solutions to research, design, and develop a data integration and analysis system that is capable of fusing unstructured (textual) and structured (machine-readable) data sources to provide a quantitative assessment (score) of the effectiveness of Naval maintenance and sustainment processes. Assessing whether existing systems and procedures are meeting their goals requires bringing together data from across multiple, disconnected silos. Much of the vital data that identifies key performance indicators, thresholds for acceptable quality or cost, or desirable outcomes are only available in unstructured text documents. We propose a system that allows users with no prior experience in Natural Language Processing (NLP) or Information Extraction (IE) practices to interact with an automated system that learns over time how to extract the data they require. This data, in turn, feeds a scoring capability that allows users to construct and monitor quantitative measures of the effectiveness of existing or planned sustainment practices. Such data can then been used to provide meaningful, objective information to support process improvement initiatives. Benefits: Our proposed solution provides a system that allows users to extract requirements, performance criteria, and other desirable quantities from unstructured text sources. For many organizations, key requirements are often only recorded in such documents but never explicitly recorded as quantifiable metrics. We envision that such a system that is capable of "promoting" textual requirements into measurable quantities of interest has broad applicability in a number of industries. Some potential commercial applications include scoring resumes against position requirements for technical recruiters and human resource professionals; scoring vendors' proposals against the requirements listed in a Request for Proposal or Statement of Work for contracting organizations; evaluating whether existing procedures satisfy legal or regulatory requirements for organizations in highly regulated industries. Return