IBminer: A Text Mining Tool for Constructing and Populating InfoBox Databases and Knowledge Bases
Knowledge bases and structured summaries are playing a crucial role in many applications, such as text summarization, question answering, essay grading, and semantic search. Although, many systems (e.g. DBpedia and YaGo2) provide massive knowledge bases of such summaries, they all suffer from incompleteness, inconsistencies, and inaccuracies. These problems can be addressed and much improved by combining and integrating different knowledge bases, but their very large sizes and their reliance on different terminologies and ontologies make the task very difficult. In this demo, we will demonstrate a system that is achieving good success on this task by: i) employing available interlinks in the current knowledge bases (e.g. externalLink and redirect links in DBpedia) to combine information on individual entities, and ii) using widely available text corpora (e.g. Wikipedia) and our IBminer text mining system, to generate and verify structured information, and reconcile terminologies across different knowledge bases. We will also demonstrate two tools designed to support the integration process in close collaboration with IBminer. The first is the InfoBox Knowledge Base Browser (IBKB) which provides structured summaries and their provenance, and the second is the InfoBox Editor (IBE) which is designed to suggest relevant attributes for a user specified subject, whereby the user can easily improve the knowledge base without requiring any knowledge about the internal terminology of individual systems.
Proc. VLDB Endow.