LIMES: A Framework for Link Discovery on the Semantic Web

Abstract The Linked Data paradigm builds upon the backbone of distributed knowledge bases connected by typed links. mere volume current as well their sheer number pose two major challenges when aiming to support computation links across and within them. first is that tools for link discovery have be time-efficient they compute Secondly, these produce high quality serve applications built well. Solutions second problem build efficient computational approaches developed solve combine with dedicated machine learning techniques. version Limes framework product seven years research on challenges. A series techniques were integrated into this address problem. combines diverse algorithms a generic extensible architecture. In article, we give an overview 1.7.4 open-source release framework. particular, focus architecture framework, intuition its inner workings brief it contains. Some descriptions which was used complete paper. Our available under GNU license at https://github.com/dice-group/LIMES together user manual developer manual.