Cedal slides. Web Inteligence 2017

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Andre Valdestilhas, Tommaso Soru, and Axel-Cyrille Ngonga Ngomo propose CEDAL, a time-efficient approach for detecting erroneous links in large-scale link repositories. CEDAL uses union-find and graph partitioning to scale to millions of links in O(mlogn) time, improving over the state of the art which has O(n^2) complexity. Experiments show CEDAL outperforms existing approaches and is able to parallelize processing across CPU and GPU cores. The authors conclude CEDAL provides an efficient way to maintain link consistency in large knowledge bases.

CEDAL: Time-Eﬃcient Detection of Erroneous Links in
Large-Scale Link Repositories
Andre Valdestilhas1 Tommaso Soru1 Axel-Cyrille Ngonga Ngomo2
1University of Leipzig 2University of Paderborn
August 23, 2017
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 1 / 13

Introduction
LODCloud has billions of links
Errors in those links can lead to applications failing completely.
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 2 / 13

Example of error types
Error type (1):
———————————-
Semantic accuracy.
(Not) represent correctly real world
facts.
Error type (2):
———————————-
Consistency & Conciseness.
(Not) free of contradictions &
minimization of redundancy.
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 3 / 13

State of the art & CEDAL Approach
State of the art:
Closures (reﬂexive, symmetric and transitive).
Not scale to millions of links.
O(n2).
CEDAL:
Union-Find (Graph-partition + Adjacency
Lists).
O(mlogn).
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 4 / 13

CEDAL Approach
Semantics of URI + Eﬃcient Graph Partition (Union-ﬁnd)
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 5 / 13

Parallel processing
CEDAL CPU/GPU processing.
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 6 / 13

Experiments & Results
State of the art
103 104 105 106
102
104
106
108
Input size (triples)
Time(ms)
Pellet
ClosureGenerator
CEDAL (Graph Partition)
O(n2) vs O(m log n)
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 7 / 13

Experiments & Results
Link Types
Property Triples
sameAs 19,606,657 (with duplicates)
country 1,309
author 766
spokenIn 624
locatedIn 250
exactMatch 167
near 30
spatial#P 28
seeAlso 14
organism 14
made 4
Links from LinkLion (http://www.linklion.org).
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 8 / 13

Experiments & Results
Runtime
2 4 6 8
0.2
0.3
0.4
0.5
0.6
Cores
Time(seconds)
(a) 1, 000 Links.
2 4 6 8
10
20
30
Cores
GPU
CPU
(b) 1, 000, 000 Links.
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 9 / 13

Experiment & Results
Knowledge bases ranking
0 10000 20000 30000 40000 50000 60000
Erroneous candidates
rkbexplorer.dotac---rkbexplorer.eprints
d-nb.info---viaf.org
dblp.rkbexplorer.com---dblp.l3s.de
linkedgeodata.org---sws.geonames.org
citeseer.rkbexplorer.com---kisti.rkbexplorer.com
Linksetknowledgebase
Top 5 Knowledge-base pairs with more erroneous candidates.
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 10 / 13

Provenance of the links
Comparison of results with respect to the provenance of the links
Framework Errors Resources M1
sameas.org 3,792,326 28,130,994 0.865
LIMES 1,130 27,819 0.951
Silk 5,933 208,300 0.972
DBpedia Extraction Framework 12,615 914,180 0.986
M1 is the metric for linkset quality measure.M1 = P∈P− |P|
P∈P |P|
SameAs.org Limes Silk DBpedia Extraction Framework
0.00%
2.00%
4.00%
6.00%
8.00%
10.00%
12.00%
14.00%
Erroneouscandidates
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 11 / 13

Conclusions and Future work
An approach for consistency without processing the closures
Track the consistency problems
Scalable (CPU / GPU)
Study case with LinkLion
Quality measure
Future work: Applications (LinkLion2 and Education)
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 12 / 13

The end
Thanks !
Questions ?
—————
Contact:
valdestilhas@informatik.uni-leipzig.de
tsoru@informatik.uni-leipzig.de
axel.ngonga@upb.de
https://github.com/dice-group/CEDAL
Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 13 / 13

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Artificial Intelligence, Data and Competition – SCHREPEL – June 2024 OECD dis...

OECD Directorate for Financial and Enterprise Affairs

This presentation by Thibault Schrepel, Associate Professor of Law at Vrije Universiteit Amsterdam University, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp. This presentation was uploaded with the author’s consent.

怎么办理(lincoln学位证书)英国林肯大学毕业证文凭学位证书原版一模一样

kekzed

原版定制【微信:bwp0011】《(lincoln学位证书)英国林肯大学毕业证文凭学位证书》【微信:bwp0011】成绩单、雅思、外壳、留信学历认证永久存档查询，采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。【业务选择办理准则】一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信bwp0011】文凭即可二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信bwp0011】即可三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才【关于价格问题（保证一手价格）】我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子我给客户的都是第一手的代理价格，因为我想坦诚对待大家不想跟大家在价格方面浪费时间对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。

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Cedal slides. Web Inteligence 2017

1. CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link Repositories Andre Valdestilhas1 Tommaso Soru1 Axel-Cyrille Ngonga Ngomo2 1University of Leipzig 2University of Paderborn August 23, 2017 Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 1 / 13

2. Introduction LODCloud has billions of links Errors in those links can lead to applications failing completely. Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 2 / 13

3. Example of error types Error type (1): ———————————- Semantic accuracy. (Not) represent correctly real world facts. Error type (2): ———————————- Consistency & Conciseness. (Not) free of contradictions & minimization of redundancy. Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 3 / 13

4. State of the art & CEDAL Approach State of the art: Closures (reﬂexive, symmetric and transitive). Not scale to millions of links. O(n2). CEDAL: Union-Find (Graph-partition + Adjacency Lists). O(mlogn). Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 4 / 13

5. CEDAL Approach Semantics of URI + Efficient Graph Partition (Union-find) Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Efficient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 5 / 13

6. Parallel processing CEDAL CPU/GPU processing. Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 6 / 13

7. Experiments & Results State of the art 103 104 105 106 102 104 106 108 Input size (triples) Time(ms) Pellet ClosureGenerator CEDAL (Graph Partition) O(n2) vs O(m log n) Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 7 / 13

8. Experiments & Results Link Types Property Triples sameAs 19,606,657 (with duplicates) country 1,309 author 766 spokenIn 624 locatedIn 250 exactMatch 167 near 30 spatial#P 28 seeAlso 14 organism 14 made 4 Links from LinkLion (http://www.linklion.org). Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 8 / 13

9. Experiments & Results Runtime 2 4 6 8 0.2 0.3 0.4 0.5 0.6 Cores Time(seconds) (a) 1, 000 Links. 2 4 6 8 10 20 30 Cores GPU CPU (b) 1, 000, 000 Links. Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 9 / 13

10. Experiment & Results Knowledge bases ranking 0 10000 20000 30000 40000 50000 60000 Erroneous candidates rkbexplorer.dotac---rkbexplorer.eprints d-nb.info---viaf.org dblp.rkbexplorer.com---dblp.l3s.de linkedgeodata.org---sws.geonames.org citeseer.rkbexplorer.com---kisti.rkbexplorer.com Linksetknowledgebase Top 5 Knowledge-base pairs with more erroneous candidates. Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 10 / 13

11. Provenance of the links Comparison of results with respect to the provenance of the links Framework Errors Resources M1 sameas.org 3,792,326 28,130,994 0.865 LIMES 1,130 27,819 0.951 Silk 5,933 208,300 0.972 DBpedia Extraction Framework 12,615 914,180 0.986 M1 is the metric for linkset quality measure.M1 = P∈P− |P| P∈P |P| SameAs.org Limes Silk DBpedia Extraction Framework 0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% 14.00% Erroneouscandidates Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 11 / 13

12. Conclusions and Future work An approach for consistency without processing the closures Track the consistency problems Scalable (CPU / GPU) Study case with LinkLion Quality measure Future work: Applications (LinkLion2 and Education) Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 12 / 13

13. The end Thanks ! Questions ? ————— Contact: valdestilhas@informatik.uni-leipzig.de tsoru@informatik.uni-leipzig.de axel.ngonga@upb.de https://github.com/dice-group/CEDAL Andre Valdestilhas, Tommaso Soru, Axel-Cyrille Ngonga Ngomo (Universities of Somewhere and Elsewhere)CEDAL: Time-Eﬃcient Detection of Erroneous Links in Large-Scale Link RepositoriesAugust 23, 2017 13 / 13

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