SBIR Phase I: Quality-Based Knowledge Discovery for Information Retrieval in Large Organizations

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This Small Business Innovation Research Phase I project will determine the feasibility of a novel, powerful technique to determine the quality of documents and the reliability of human reviewers in a large community, such as a company, government agency (particularly intelligence organizations), or university. Many organizations have difficulty locating their own knowledge. They cannot determine the quality of their internal documents nor the ability of their employees to evaluate those documents. Important information may get buried in layers of bureaucracy. This research seeks to address these problems by measuring document quality and user reputation, based on human evaluation and automated processing of those evaluations. The research objectives are: study and refinement of information theoretic techniques underlying the current technology; discovery of practical designs for expanding its scope; and creation of proof-of-concept demonstrations. The research will produce technical papers describing such systems and prove them feasible through software. Potential applications include stand-alone knowledge management products focused on document quality and plug-ins to add this capability to existing KM systems. Members of communities using these products will find the information they need more quickly and with greater confidence, enhancing efficiency and effectiveness in corporations, academic institutions, and government agencies.The research will lead to marketable knowledge management software products and/or services which offer quality-based knowledge discovery and are targeted to large organizations in any sector (business, public, academic, or not-for-profit). This technology is not another kind of search engine. It is an evaluation system that identifies the best sources of knowledge, and the most valuable knowledge items, based on the experience of the users in the community. Today there are many vendors providing a variety of knowledge management solutions to large organizations, but we know of none that offers a knowledge discovery solution based on quality.