TAKODO: Integrating documents with knowledge bases for information retrieval and knowledge management.

Abstract

The expanding availability of on-line information sources, such as on-line documents, corpora, and the World Wide Web, introduces some challenges. Most notably, users must search through this material to find high-quality, relevant information. This is the domain of information retrieval. Alternatively, knowledge bases present information in a very compact and structured representation. Unfortunately, their creation is labor intensive. In order to bridge the gap between the amount of structure in the information processed by information retrieval and knowledge engineering techniques, the author presents TAKODO, a tool and a framework designed for both (i) facilitating the extraction of knowledge from unstructured text, possibly to aid in the process of creating a knowledge base, and (ii) retrieving information from natural language texts and the knowledge base, using each to their mutual advantage. TAKODO integrates several existing applications, among them a question answering system, called Text Analyzer, and a frame-based knowledge management tool, called the Knowledge Organizer, with the additional support of corpus linguistic techniques.