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Welcome to LD4KD 2015#LD4KD2015
Ilaria Tiddi - @IlaTiddiMathieu d’Aquin - @mdaquinClaudia d’Amato - @cldamat
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Yes, this is a small workshop...
2 paper presentations out of 4 papers submitted
but
A lot of interest from both communities (KD/ML and Linked Data).LD4KD is more than a set of paper presentations.
Working on existing opportunities and challenges and the way they can be better supported/addressed.
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Program10:00 – 10:15 Welcome10:15 – 10:45 Linked Data for Knowledge Discovery: the story so far
10:45 – 11:15 Mehwish Alam and Amedeo Napoli, Navigating and Exploring RDF Data using Formal Concept Analysis
11:15 – 11:30 Coffee Break
11:30 – 12:00 Denis Krompaß and Volker Tresp, Ensemble Solutions for Link-Prediction in Knowledge Graphs
12:00 – 12:45 Demo session12:45 – 13:00 Wrap-up and conclusions
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Linked Data for Knowledge Discovery: the story so far
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LD for KD - KD with LD
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LD for KD - KD with LD
A set of te
chniques and methods to
extract m
eaningful inform
ation
patterns fro
m raw data
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LD for KD - KD with LD
A set of te
chniques and methods to
extract m
eaningful inform
ation
patterns fro
m raw data
A set of p
rinciples and te
chnologies
for sharin
g and integratin
g data
through the archite
cture of the W
eb
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LD for KD - KD with LD
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LD for KD - KD with LD
A complex,
information-in
tensive
process
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LD for KD - KD with LD
A complex,
information-in
tensive
process A global, distrib
uted
and collaborative
informatio
n source
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LD for KD - KD with LD
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LD for KD - KD with LD
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LD for KD - KD with LD
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LD for KD - KD with LD
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LD for KD - KD with LD
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LD for KD - KD with LD
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LD for KD - KD with LD
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Needs a more systematic understanding...Of the way the properties of the process of KD and of the information source of LD create new opportunities and challenges for both communities.
Knowledge Discovery Linked Data
Talking about communities: ?
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Started in LD4KD 2014http://events.kmi.open.ac.uk/ld4kd2014/
http://goo.gl/NEu1d7
A collaborative document to share information about issues, challenges, tools and methods at the intersection of Linked Data and Knowledge Discovery
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Opportunities Linked Data as Input
Large, global, accessible, convenient, multilingual - Separation of data and process - Easily extended, integrated, enriched.
Link Discovery Using DM/ML techniques to find connections across disparate datasetsExploiting links across dataset for richer data, and richer patternsCan this be done “on the fly”, i.e. within DM/ML process?
Background knowledge to enrich the KDD processCan Linked Data be part of the bottom arrow in the KDD diagram? A global, universally accessible knowledge base of almost everything?
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Is it too hard?
“RDF and SPARQL - are they really complicated?”
“Not really, but SPARQL is not what ML researchers want to worry about. Most of us don't even like SQL. Just a CSV file is the easiest format. It's messy, but we really don't care.”
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ChallengesLinked data is a graph
but is this really an issue?
Linked data is a distributed, collaborative graph accessibility issues, link explosion, terminationneed to build the graph on the fly, not all data is known at the start
Linked data is incomplete and biasedAnd we don’t know the bias - how to evaluate KDD that uses Linked Data?
Linked data is redundant, unbalanced and unreliablenoisy, bad formating (no control), lack of documentation, which ID/source to choose and what is the impact?
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And we haven’t even started talking about...
Mr. Slow
and
Mr. Nosey
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Continuing this year...Start with the practical aspects: What tools and applications exist, through which we can explore the use of linked
data in KD, and from which we can learn how to solve some of the challenges
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Discuss, Contribute, Questionand of course
Enjoy the workshop!#LD4KD2015