Research Information System
4th International Workshop on Intelligent Exploration of Semantic Data, IESD 2015 - co-located with the 14th International Semantic Web Conference, ISWC 2015, Pennsylvania, United States Of America, 12 October 2015, vol.1472, (Full Text)
In this current study, we use graph localities and neighbor-hood similarity to enhance the summary graph generation approach for building a summary graph structure for intelligent exploration of semantic data. The key improvements to what we have previously proposed include the addition of a string similarity measure for the literal neighbors, development of a stability measure to evaluate the accuracy of class relations, the addition of auto-generated property weights, and the detection of noise properties.