ConNeKTion: A Tool for Handling Conceptual Graphs Automatically Extracted from Text

Abstract

Studying, understanding and exploiting the content of a digital library, and extracting useful information thereof, require automatic techniques that can effectively support the users. To this aim, a relevant role can be played by concept taxonomies. Unfortunately, the availability of such a kind of resources is limited, and their manual building and maintenance are costly and error-prone. This work presents ConNeKTion, a tool for conceptual graph learning and exploitation. It allows to learn conceptual graphs from plain text and to enrich them by finding concept generalizations. The resulting graph can be used for several purposes: finding relationships between concepts (if any), filtering the concepts from a particular perspective, extracting keyword, retrieving information and identifying the author. ConNeKTion provides also a suitable control panel, to comfortably carry out these activities. © Springer-Verlag Berlin Heidelberg 2014.