The LIMES development team is happy to announce LIMES 1.5.5!

LIMES is a link discovery framework for the Web of Data, which implements time-efficient approaches to discover links among RDF resources. LIMES attempts to harness similarity measures in many dimensions including (but not limited to) the euclidean, spatial and temporal dimensions. Our framework provides a cross-platform graphical user interface as well as several machine learning algorithms which enable an easy configuration of the link discovery tasks.
 

These are the new LIMES developments since our last software release:

• Added 2 phonetic string similarity measures (Koeln & DoubleMetaphone)
• Added the beta (β) parameter to all implementations of the Wombat machine learning algorithm. Use this parameter to set how Precision and Recall are weighted in the Fᵦ-measure which is used as fitness function in Wombat.
• Improvement of the evaluation package
• Implemented a quality indicator feature
• Restructured user manual to allow for a quick start with LIMES
• Several bug fixes

Get the newest release here, see our previous blog post for more in-depth details and stay tuned for our next LIMES releases!