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Exploring Importance Measures for Summarizing RDF/S KBs
Published on Jul 10, 2017782 Views
Given the explosive growth in the size and the complexity of the Data Web, there is now more than ever, an increasing need to develop methods and tools in order to facilitate the understanding and exp
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Chapter list
Exploring Importance Measures for Summarizing RDF/S KBs00:00
Structure00:10
Problem Definition00:29
Summarization01:00
Graph01:20
Graph - 101:41
Central questions to the process of summarization02:01
Importance Measures02:46
Graph Instance03:13
Degree03:30
Ego03:47
Betweenness04:11
Bridging Centrality04:25
Harmonic04:33
Radiality04:40
Summarized Importance Value06:07
Related Work - Relevance06:49
Related Work – KCE importance07:10
Construction of the RDF/S Summary Schema Graph07:37
The Steiner Tree Problem08:03
Algorithms, Approximation & Heuristics08:49
Complexity of Algorithms09:24
The competitor - The Maximum-Cost Spanning Tree (MST)09:36
Evaluation - Data Sets10:13
Evaluation - Gold Standard11:21
Evaluation - Measures12:02
Spearman’s rank correlation coefficient12:50
The Similarity Measure13:07
Graph edit distance13:36
Additional vertices Introduced13:55
Execution Time14:16
Spearman’s rank correlation coefficient14:29
The Similarity Measure15:49
Additional vertices Introduced16:22
Average Execution Time in milliseconds16:50
Discussion & Conclusion17:46
Future Work19:10