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BipRank: Ranking and Summarizing
RDF Vocabulary Descriptions
Gong Cheng1, Feng Ji2, Shengmei Luo2, Weiyi Ge1, Yuzhong Qu1
1State Key Laboratory for Novel Software Technology, Nanjing University, China
2Communication Services R&D Institute, ZTE Corporation, China
Presented at JIST2011

2. Outline
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Introduction
Salience measurement
Vocabulary summarization
Conclusions
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3. Vocabularies and Linked Data
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Vocabularies Your own vocabulary
Reuse
Linked Data
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4. Vocabulary search engines
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5. Vocabularies
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Scale
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6. Vocabulary snippets --- state of the art
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7. Vocabulary snippets --- our approach
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8. Vocabulary summarization
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Vocabulary summarization = ranking and selecting RDF sentences
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9. Outline
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Introduction
Salience measurement
Vocabulary summarization
Conclusions
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10. A bipartite view of vocabulary description
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11. Surfer behavior --- type A
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12. Surfer behavior --- type B
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13. BipRank
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Next step ? Uniform Current step
type-A behavior
type-B behavior
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14. Pattern of RDF sentence
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15. p(s|u)
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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 pattern
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16. Evaluation setting
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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 coefficient
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17. Evaluation results
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18. Outline
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Introduction
Salience measurement
Vocabulary summarization
Conclusions
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19. Goodness of a summary
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Salience
Query relevance
Textual similarity between query and summary
Cohesion
Term overlap between RDF sentences
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20. Looking for the best summary
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Multi-objective optimization
Single aggregate objective function
Solution: a greedy strategy
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21. Evaluation setting
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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 scale
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22. Evaluation results
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23. Performance testing
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Size of summary Runtime
Size of vocabulary
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24. Outline
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Introduction
Salience measurement
Vocabulary summarization
Conclusions
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25. Conclusions
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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/
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