Extracting conceptual relationships from specialized documents

Abstract

Conceptual modeling has been fundamental to the management of structured data. However, its value is increasingly being recognized for knowledge management in general. In trying to develop suitable conceptual models for unstructured information, issues such as the level of representation and complexity of processing techniques arise. Here, we investigate the use of a conceptual model that is simple enough to allow efficient automatic extraction from documents. Our model focused on the problem-solution relationship that is central to the analysis of scientific papers. It also consists of supporting relationships such as benefits and drawbacks, assumptions, methods, extensions, and claims. Our study considered two kinds of documents-scientific research papers and patents. We evaluated the utility of the approach by building a prototype system and our user evaluation shows promising results.