Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
DRETa: Extracting RDF from Wikitables [POSTER]
Search
Emir Muñoz
October 23, 2013
Research
0
58
DRETa: Extracting RDF from Wikitables [POSTER]
DRETa: Extracting RDF from Wikitables
Posters & Demos @ ISWC 2013
Emir Muñoz
October 23, 2013
Tweet
Share
More Decks by Emir Muñoz
See All by Emir Muñoz
Machine Learning Pipelines in Production - ML Galway Meetup
emunoz
0
60
Academic Writing: Hints and Tools
emunoz
0
140
Mining Cardinalities from Knowledge Bases
emunoz
0
180
Using Drug Similarities for Discovery of Possible Adverse Reactions
emunoz
0
110
A Hybrid Method for Rating Prediction Using Linked Data Features and Text Reviews
emunoz
0
180
On Learnability of Cardinality Constraints from RDF Data
emunoz
0
130
Minute Madness ESWC 2016
emunoz
0
100
Tensor Networks---a brief description
emunoz
0
75
A Linked Data-Based Decision Tree Classifier to Review Movies
emunoz
1
180
Other Decks in Research
See All in Research
IM2024
mamoruk
0
230
Large Vision Language Model (LVLM) に関する最新知見まとめ (Part 1)
onely7
24
6k
VisFocus: Prompt-Guided Vision Encoders for OCR-Free Dense Document Understanding
sansan_randd
1
470
打率7割を実現する、プロダクトディスカバリーの7つの極意(pmconf2024)
geshi0820
0
360
【NLPコロキウム】Stepwise Alignment for Constrained Language Model Policy Optimization (NeurIPS 2024)
akifumi_wachi
3
540
「熊本県内バス・電車無料デー」の振り返りとその後の展開@土木計画学SS:成功失敗事例に学ぶ公共交通運賃設定
trafficbrain
0
230
国際会議ACL2024参加報告
chemical_tree
1
440
精度を無視しない推薦多様化の評価指標
kuri8ive
1
370
Poster: Feasibility of Runtime-Neutral Wasm Instrumentation for Edge-Cloud Workload Handover
chikuwait
0
360
書き手はどこを訪れたか? - 言語モデルで訪問行動を読み取る -
hiroki13
0
150
Human-Informed Machine Learning Models and Interactions
hiromu1996
2
580
Bluesky Game Dev
trezy
0
160
Featured
See All Featured
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
29
2.5k
The Invisible Side of Design
smashingmag
299
50k
Visualization
eitanlees
146
15k
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
4
390
Building Better People: How to give real-time feedback that sticks.
wjessup
367
19k
Building a Modern Day E-commerce SEO Strategy
aleyda
38
7.1k
The Language of Interfaces
destraynor
156
24k
A Tale of Four Properties
chriscoyier
158
23k
Gamification - CAS2011
davidbonilla
80
5.2k
A designer walks into a library…
pauljervisheath
205
24k
Statistics for Hackers
jakevdp
797
220k
Embracing the Ebb and Flow
colly
84
4.6k
Transcript
Enabling Networked Knowledge ACKNOWLEDGEMENTS: This work was funded in part
by Science Foundation Ireland under Grant No. SFI/08/CE/I1380 (Lion-2). DRETA: EXTRACTING RDF FROM WIKITABLES Emir Muñoz, Aidan Hogan, Alessandra Mileo National University of Ireland, Galway MOTIVATION WIKITABLE SURVEY player http://dbpedia.org/resource/David_de_Gea http://dbpedia.org/resource/Rafael_Pereira_da_Silva_(footballer_born_1990) http://dbpedia.org/resource/Patrice_Evra …. http://dbpedia.org/resource/Fabio_Pereira_da_Silva http://dbpedia.org/resource/Tom_Cleverley http://dbpedia.org/resource/Darren_Fletcher PROPOSAL http://dbpedia.org/resource/Manchester_United_F.C. http://dbpedia.org/resource/England http://dbpedia.org/resource/Forward_(association_football) http://dbpedia.org/resource/Wayne_Rooney dbo:birthPlace dbp:currentclub dbp:position http://dbpedia.org/resource/Spain http://dbpedia.org/resource/Goalkeeper_(association_football) http://dbpedia.org/resource/David_de_Gea dbp:position http://dbpedia.org/resource/Brazil http://dbpedia.org/resource/Defender_(association_football) http://dbpedia.org/resource/Fabio_Pereira_da_Silva dbp:position … … (1) dbr:David_de_Gea dbo:birthPlace dbr:Spain . (2) dbr:Fabio_Pereira_de_Silva dbo:birthPlace dbr:Brazil . (3) dbr:Fabio_Pereira_de_Silva dbp:currentclub dbr:Manchester_United_F.C . SUGGESTED TRIPLES: SELECT ?player WHERE { ?player dbp:currentclub dbr:Manchester_United_F.C . } TABLE TAXONOMY: DISTRIBUTIONS: QUERY: RESULTS DEMO … http://emunoz.org/wikitables (1) EXTRACTED 34.9 MILLION UNIQUE & NOVEL TRIPLES FROM 1.14 MILLION WIKITABLES (8 MACHINES: 4GB RAM, 2.2 GHZ SINGLE CORE; 12 DAYS) (2) INITIAL EVALUATION: (MANUAL ANNOTATION; THREE JUDGES; 750 TRIPLES EACH) (3) MACHINE LEARNING CLASSIFIERS: (CONSENSUS GOLD STANDARD; VARIETY OF FEATURES) FROM 1.14 MILLION WIKITABLES: BAGGING DECISION TREES: SUPPORT VECTOR MACHINES: 1.14 MILLION WIKITABLES: 7.9 MILLION TRIPLES @81.5% PREC. 15.3 MILLION TRIPLES @72.4% PREC. … INCOMPLETE RESULTS!