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
57
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
53
Academic Writing: Hints and Tools
emunoz
0
140
Mining Cardinalities from Knowledge Bases
emunoz
0
150
Using Drug Similarities for Discovery of Possible Adverse Reactions
emunoz
0
93
A Hybrid Method for Rating Prediction Using Linked Data Features and Text Reviews
emunoz
0
160
On Learnability of Cardinality Constraints from RDF Data
emunoz
0
110
Minute Madness ESWC 2016
emunoz
0
96
Tensor Networks---a brief description
emunoz
0
63
A Linked Data-Based Decision Tree Classifier to Review Movies
emunoz
1
150
Other Decks in Research
See All in Research
FOSS4G 山陰 Meetup 2024@砂丘 はじめの挨拶
wata909
1
110
文化が形作る音楽推薦の消費と、その逆
kuri8ive
0
160
言語と数理の交差点:テキストの埋め込みと構造のモデル化 (IBIS 2024 チュートリアル)
yukiar
3
730
Isotropy, Clusters, and Classifiers
hpprc
3
630
20240820: Minimum Bayes Risk Decoding for High-Quality Text Generation Beyond High-Probability Text
de9uch1
0
120
20240918 交通くまもとーく 未来の鉄道網編(こねくま)
trafficbrain
0
230
Geospecific View Generation - Geometry-Context Aware High-resolution Ground View Inference from Satellite Views
satai
1
100
情報処理学会関西支部2024年度定期講演会「自然言語処理と大規模言語モデルの基礎」
ksudoh
3
370
文書画像のデータ化における VLM活用 / Use of VLM in document image data conversion
sansan_randd
2
190
非ガウス性と非線形性に基づく統計的因果探索
sshimizu2006
0
360
Language is primarily a tool for communication rather than thought
ryou0634
4
740
工学としてのSRE再訪 / Revisiting SRE as Engineering
yuukit
19
11k
Featured
See All Featured
We Have a Design System, Now What?
morganepeng
50
7.2k
Adopting Sorbet at Scale
ufuk
73
9.1k
How to Create Impact in a Changing Tech Landscape [PerfNow 2023]
tammyeverts
47
2.1k
Bash Introduction
62gerente
608
210k
[RailsConf 2023] Rails as a piece of cake
palkan
52
4.9k
Designing for Performance
lara
604
68k
Build your cross-platform service in a week with App Engine
jlugia
229
18k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
26
2.1k
The Success of Rails: Ensuring Growth for the Next 100 Years
eileencodes
44
6.8k
The Cult of Friendly URLs
andyhume
78
6k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
364
24k
Designing Dashboards & Data Visualisations in Web Apps
destraynor
229
52k
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!