introduction to urban computing in larkc
DESCRIPTION
Introduction to the seminar hold in Cefriel to present some of the results from the Urban Computing use case of the LarKC projectTRANSCRIPT
Introduction to Urban Computing in LarKC – Cefriel, 28th June 2011
Urban Computing in LarKC
Irene Celino, Daniele Dell’Aglio, Emanuele Della Valle
CEFRIEL – ICT Institute, Politecnico di Milano
LarKC – the vision
Web-scale Data
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1 triple:
Distance Sun – Pluto ~1014 triples (estimate on
no. triples on the Web)
See also: http://www.youtube.com/watch?v=hjUbbl4cnAE
LarKC – the vision
Web-scale Reasoning
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prec
isio
n (s
ound
ness
)
recall (completeness)
Logics
IR
Semantic Web
� Giving up 100% correctness:� trading quality for size� often completeness is
not needed� sometimes even
correctness is not needed
� � not only logics!
See also: http://www.youtube.com/watch?v=hjUbbl4cnAE
The LarKC project
� LarKC – the Large Knowledge Collider – is a platform for massive distributed incomplete reasoning to remove the scalability barriers of existing reasoning systems for the Semantic Web
� Technology pillars:� logic-based reasoning � information retrieval� machine learning� databases� probabilistic reasoning� cognitively-inspired approaches � high-performance computing
Factsheet:� 10M€ budget� 3.5 years (ending Sept 2011)� >80 person years� 16 partners, 3 use case � obtained in FP7 Call1
Outcomes:� LarKC Platform on
Sourceforge (now v 2.5) with Apache license
� >25 plug-ins for the platform� Several demonstrators� >90 publications
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http://www.larkc.eu/
http://www.youtube.com/watch?v=hjUbbl4cnAE
The integration of computing, sensing, and actuation technologies into everyday urban settings and lifestyles.
Urban Computing
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[source IEEE Pervasive Computing,July-September 2007 (Vol. 6, No. 3)]
� Urban settings include streets, squares, pubs, shops, buses, and cafés - any space in the semipublic realms of our towns and cities
� Only in the last few years research paid attention to urban environments
� Pervasive computing is more and more applied � Great success of Location-based Services and Location-based Social
Networks with increasing amounts of data
� � Urban settings are challenging for experimentation & deployment
LarKC Urban Computing Use Case
� Urban Computing to address cities' challenges� LarKC to elaborate urban data and provide solutions
Is public transportation where the people are?
Which landmarks attract more people?
Where are people concentrating?
Where is traffic moving?
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"Semantics" in the LarKC Urban Computing use case
Semantic Technologies
� Semantic Points of Interest (POIs) retrieval:
� Which are the relevant monuments? What events are scheduled tonight? What POIs should I visit?
� Operations Research:
� What is the most "desirable" path to my destination (shortest vs. quickest)? How should I schedule my city tour given my time constraints (TSP problem)?
� Machine Learning:
� What POIs could be interesting for me? Should I expect traffic on my way to…? Which "mavens" of this POI should I ask for advice?
� RDF/SPARQL/OWL based interoperability:
� integration and interoperability between different components through the adoption of Semantic Web technologies (enabled by the LarKC platform)
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� Year 1:� Urban LarKC: find monuments and events in Milano and the
shortest path to reach them
LarKC Urban Computing Demonstrators
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� Year 1:� Glusic: music concert recommender system based on social
streams and multimedia contents
LarKC Urban Computing Demonstrators
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� Year 2:� Korean Road Sign Management: automatic checking of road signs
information in Seoul
LarKC Urban Computing Demonstrators
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� Year 2:� Traffic LarKC: find the shortest/quickest path to your destination in
Milano with traffic predictions - http://larkc.cefriel.it/traffic-larkc
LarKC Urban Computing Demonstrators
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� Year 3:� BOTTARI: Location-based Social Media Analytics on Seoul POIs
LarKC Urban Computing Demonstrators
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� Year 1:� Urban LarKC: find monuments and events in Milano and the shortest
path to reach them� Glusic: music concert recommender system based on social streams
and multimedia contents
� Year 2:� Korean Road Sign Management: automatic checking of road signs
information in Seoul� Traffic LarKC: find the shortest/quickest path to your destination in
Milano with traffic predictions
� Year 3:� BOTTARI: Location-based Social Media Analytics on Seoul POIs� Semantic City Tour Planner: Travel Salesman Problem with Time
Windows (TSP-TW) with dynamic Semantic POI retrieval in Amsterdam
LarKC Urban Computing Demonstrators
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What's next today?
� Semantic City Tour Planner: Travel Salesman Problem with Time Windows (TSP-TW) with dynamic Semantic POI retrieval in Amsterdam� Master Thesis work of Chris and Bas from the Vrije Universiteit
Amsterdam � Participating to the LarKC Workflow Challenge
http://www.larkc.eu/larkc-workflow-challenge-2011/
� Traffic LarKC: find the shortest/quickest path to your destination in Milano with traffic predictions� Collaboration between CEFRIEL and Siemens in LarKC� Winner of the AI Mashup Challenge 2011
https://sites.google.com/a/fh-hannover.de/aimashup11/
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Thanks for your attention! Any question?
Contact: Irene Celino – Semantic Web Practice
CEFRIEL – ICT Institute, Politecnico di Milanoemail: [email protected] – web: http://swa.cefriel.it
personal website: http://iricelino.org
phone: +39-02-23954266 – fax: +39-02-23954466
slides available at: http://www.slideshare.net/iricelino
Introduction to Urban Computing in LarKC – Cefriel, 28th June 2011