This Small Business Innovation Research (SBIR) Phase I Project addresses the gap between the capabilities of today's natural language processing systems and the accuracy requirements of knowledge workers (analysts and researchers) in language-sensitive fields such as public relations, foreign affairs, and crisis management. Knowledge workers in many organizations monitor and analyze print and web coverage for content of interest. When the volume of search results is large, some filter, classify and score the results with Natural Language Processing (NLP) systems using complex libraries of words, patterns, and context-specific algorithms. However, users complain that these systems fall short of desired accuracy, missing rhetorical devices such as irony, sarcasm, metaphors, double entendre, and improperly interpreting references. Users with high thresholds for accuracy thus turn to manual processes to either supplement or substitute for technology. This project will test a prototype architecture allowing rapid insertion, testing, and adaptation of text analysis algorithms and a workflow process efficiently integrating human review judgment.
Once commercialized, the system will enable more rapid adoption of technology by knowledge workers. In fields with high accuracy requirements, the need for human judgment has constrained technology use to discrete areas like search, while in subsequent processing steps, analysts must manually capture, classify, score, analyze, and report on the output.
In our Small Business Innovation Research Phase I Project, we began to address the gap between the capabilities of today’s natural language processing systems and the accuracy requirements of knowledge workers in language-sensitive fields. We developed a prototype content processing technology based on modules that could be plugged into a workflow process efficiently integrating human insight. During the Phase I SBIR, we successfully designed and built three content processing modules and integrated each of these modules into a working media analysis system. Based on the successful deliverables completed in this SBIR Phase I project augmented by privately funded product development work, Red Lion launched a Beta product to a major customer in the marketplace, and with continued development work we will launch a full-scale commercial product in 2011. In fields with high accuracy requirements, the need for human judgment has constrained technology use to discrete areas like search, while in subsequent processing steps, analysts must manually capture, classify, score, analyze, and report on the output. Once commercialized, our system will enable more rapid adoption of technology by knowledge workers. We focus initially on marketing, PR and communications teams, but the fundamental technology being developed has broader application to knowledge workers in other fields, including (but not limited to) markets such as brand management, crisis management, government relations, constituent outreach, foreign affairs, and homeland defense/anti-terrorism. All of these fields share similar underlying content processing challenges that our solution helps solve.
