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BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
BipRank: Ranking and Summarizing RDF Vocabulary Descriptions
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BipRank: Ranking and Summarizing RDF Vocabulary Descriptions

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  • 1. .nju.edu.cn BipRank: Ranking and Summarizing RDF Vocabulary Descriptions Gong Cheng1, Feng Ji2, Shengmei Luo2, Weiyi Ge1, Yuzhong Qu11State Key Laboratory for Novel Software Technology, Nanjing University, China 2Communication Services R&D Institute, ZTE Corporation, China Presented at JIST2011
  • 2. Outline ws .nju.edu.cn Introduction Salience measurement Vocabulary summarization ConclusionsGong Cheng (程龚) gcheng@nju.edu.cn 2 of 25
  • 3. Vocabularies and Linked Data ws .nju.edu.cn Vocabularies Your own vocabulary Reuse Linked DataGong Cheng (程龚) gcheng@nju.edu.cn 3 of 25
  • 4. Vocabulary search engines ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 4 of 25
  • 5. Vocabularies ws .nju.edu.cn ScaleGong Cheng (程龚) gcheng@nju.edu.cn 5 of 25
  • 6. Vocabulary snippets --- state of the art ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 6 of 25
  • 7. Vocabulary snippets --- our approach ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 7 of 25
  • 8. Vocabulary summarization ws .nju.edu.cn Vocabulary summarization = ranking and selecting RDF sentencesGong Cheng (程龚) gcheng@nju.edu.cn 8 of 25
  • 9. Outline ws .nju.edu.cn Introduction Salience measurement Vocabulary summarization ConclusionsGong Cheng (程龚) gcheng@nju.edu.cn 9 of 25
  • 10. A bipartite view of vocabulary description ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 10 of 25
  • 11. Surfer behavior --- type A ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 11 of 25
  • 12. Surfer behavior --- type B ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 12 of 25
  • 13. BipRank ws .nju.edu.cn Next step ? Uniform Current step type-A behavior type-B behaviorGong Cheng (程龚) gcheng@nju.edu.cn 13 of 25
  • 14. Pattern of RDF sentence ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 14 of 25
  • 15. p(s|u) ws .nju.edu.cn Frequency of Pattern(s) #RDF_sentence in the vocabulary that has the same pattern Popularity of Pattern(s) #Vocabulary in the repository that has the same patternGong Cheng (程龚) gcheng@nju.edu.cn 15 of 25
  • 16. Evaluation setting ws .nju.edu.cn Test cases 9 moderate-sized vocabularies randomly selected from Falcons Gold standard Salience given by 6 human experts Competitors Cp: Zhang et al. (WWW2007) Our approach BipRank-U: pattern-unaware BipRank-F: using pattern frequency BipRank-P: using pattern popularity Metric Pearson product-moment correlation coefficientGong Cheng (程龚) gcheng@nju.edu.cn 16 of 25
  • 17. Evaluation results ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 17 of 25
  • 18. Outline ws .nju.edu.cn Introduction Salience measurement Vocabulary summarization ConclusionsGong Cheng (程龚) gcheng@nju.edu.cn 18 of 25
  • 19. Goodness of a summary ws .nju.edu.cn Salience Query relevance Textual similarity between query and summary Cohesion Term overlap between RDF sentencesGong Cheng (程龚) gcheng@nju.edu.cn 19 of 25
  • 20. Looking for the best summary ws .nju.edu.cn Multi-objective optimization Single aggregate objective function Solution: a greedy strategyGong Cheng (程龚) gcheng@nju.edu.cn 20 of 25
  • 21. Evaluation setting ws .nju.edu.cn Judges 18 human experts Test cases 190 searches over 2,012 vocabularies crawled by Falcons Competitors Generic: Zhang et al. (WWW2007) Our approach QR: query relevance QR+S: query relevance + salience QR+C: query relevance + cohesion Metric Rating on a 10-point scaleGong Cheng (程龚) gcheng@nju.edu.cn 21 of 25
  • 22. Evaluation results ws .nju.edu.cnGong Cheng (程龚) gcheng@nju.edu.cn 22 of 25
  • 23. Performance testing ws .nju.edu.cn Size of summary Runtime Size of vocabularyGong Cheng (程龚) gcheng@nju.edu.cn 23 of 25
  • 24. Outline ws .nju.edu.cn Introduction Salience measurement Vocabulary summarization ConclusionsGong Cheng (程龚) gcheng@nju.edu.cn 24 of 25
  • 25. Conclusions ws .nju.edu.cn Salience measurement Sentence-term graph BipRank Pattern of RDF sentence Vocabulary summarization Salience Query relevance Cohesion Implemented in Falcons Ontology Search http://ws.nju.edu.cn/falcons/ontologysearch/Gong Cheng (程龚) gcheng@nju.edu.cn 25 of 25

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