Post on 08-May-2015
#MSM Making Sense of Microposts Workshop at ESWC 2011 – Heraklion, Crete, 30th May 2011
Making Sense of Location-based Micro-posts
using Stream Reasoning
Irene Celino, Daniele Dell’Aglio, Emanuele Della Valle,
Yi Huang, Tony Lee, Stanley Park and Volker Tresp
(CEFRIEL – Politecnico di Milano – Saltlux – SIEMENS)
BOTTARI Mobile Application
� Augmented Reality Application for Android� to show POI information with their respective reputation� to retrieve information on the basis of the geo-social context
� where can I find people nearby sharing my preferences? � who shall I ask for an opinion on this restaurant?
#MSM Workshop at ESWC 20112Making Sense of Location-based Micro-posts using Stream Reasoning
Gathering microposts data
� Crawling microposts� User ranking model for adaptive crawling
� using users’ influence (ranking) to find appropriate and influential microposts in real-time
� Factors to compute ranking:� Micropost frequencies� # of mentioned or retweeted microposts
� Degree of interaction with followers and followings
� # of followers
#MSM Workshop at ESWC 20114Making Sense of Location-based Micro-posts using Stream Reasoning
Gathering microposts data
� For now we’ve been crawling around� 356,000,000 messages (5,300,000 messages / day)� 1,100,000 users (14,000 users / day)
#MSM Workshop at ESWC 20115Making Sense of Location-based Micro-posts using Stream Reasoning
Sentiment Analysis – high-level view
� Sentiment analysis of microposts� Compute "quantitative" ratings for each POI� When possible, different ratings for different features of the POI
(e.g., in case of restaurants: taste, service, price, …)
#MSM Workshop at ESWC 20116Making Sense of Location-based Micro-posts using Stream Reasoning
Microposts about a specific Point of Interest
Sentiment analysisalgorithm
Computed ratings(e.g. for restaurants)
taste 7.8/10
service 4.2/10
price 6.0/10
Sentiment Analysis – how it works
Micropost message
MorphologicallyAnalyzable?
Rule based Analysis
Auto generated rules
Learneddocuments
SVMs
Syllable Kernel
Reputations for each feature
Yes No
#MSM Workshop at ESWC 20117Making Sense of Location-based Micro-posts using Stream Reasoning
� Precision tests:� Auto-generated
rules ≈ 70%� Manually-coded
rules ≈ 90%� Syllable kernel ≈ 50~60%
� Our target > 85%
Ontology modelling
#MSM Workshop at ESWC 20118Making Sense of Location-based Micro-posts using Stream Reasoning
geo:SpatialThing
sioc:UserAccountsioc:id(xsd:string)
geo:NamedPlace
twd:Tweettwd:messageID(xsd:string)
twd:messageTimeStamp(xsd:string)
sioc:creator_of
twd:talksAbout
twd:reply
twd:retweet
sioc:has_creator
twd:talksAboutNeutrally
twd:talksAboutPositively
twd:followertwd:following
twd:post
sioc:Postsioc:content(xsd:string)
twd:TwitterUsertwd:screenName(xsd:string)
twd:discuss
twd:talksAboutNegatively
Querying Microposts Dynamics with
Stream Reasoning and SPARQL with probabilities
% find people similar to me which are nearby in an interesting POI
?poi1 ?user (f:similarWithProbability(ex:Alice, ?user) AS ?p)% the user I'm looking for should be "similar" to me
STREAM <http://bottari.kr/streamOftweets> [1h STEP 10m]% from the stream of microposts of last 10 minutes
WHERE {?user twd:post { twd:talksPositivelyAbout ?poi1 } .
% target user tweeted positively about a POI?poi1 geo:lat ?lat1; geo:long ?long1 ; skos:subject ?category .
% this POI has a position and categoryex:Alice twd:post { twd:talksAbout ?poi2 } .
% current user tweeted about another POI (thus she's close to it)?poi2 geo:lat ?lat2; geo:long ?long2 ; skos:subject ?category .
% the other POI is of the same categoryFILTER( (?lat1-?lat2)<"0.1"^^xsd:float &&
(?lat1-?lat2)>"-0.1"^^xsd:float && (?long1-?long2)<"0.1"^^xsd:float &&(?long1-?long2)>"-0.1"^^xsd:float ) % the target POI is close to the current user
}ORDER BY DESC(?p)LIMIT 10
#MSM Workshop at ESWC 20119Making Sense of Location-based Micro-posts using Stream Reasoning
SELECT
FROM
Thanks for your attention! Any question?
Making Sense of Location-based Micro-posts using Stream Reasoning
Paper Authors: Irene Celino, Daniele Dell'Aglio, Emanuele Della Valle, Yi Huang, Tony Lee, Stanley Park and Volker Tresp
Contact: Irene Celino – Semantic Web Practice
CEFRIEL – ICT Institute, Politecnico di Milanoemail: irene.celino@cefriel.it – 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
#MSM Making Sense of Microposts Workshop at ESWC 2011 – Heraklion, Crete, 30th May 2011