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
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.