[Databeers] 06/05/2014 - Dani Villatoro: “Cicerone: Your venue recommendations through Twitter”
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Transcript of [Databeers] 06/05/2014 - Dani Villatoro: “Cicerone: Your venue recommendations through Twitter”
@BCNPlaces4
@jordi_aranda @djkram
@techisthenewpop @dani_agent
@dani_agent
@dani_agent
What are we going to tell you?
location based
social
in-situ
recommender system
(e.g. Cicerone! Tell me a place for coffee now! // Go to Café Las Maravillas)@dani_agent
Location based
@dani_agent
If I click “Coffee”
1 Km.
Seriously
Foursquare?
@dani_agent
Social
@dani_agent
In Situ
@dani_agent
• My friends’ opinions matter.
• Experts’s opinions matter even more.
• Easy to query.– Not another app!
Requirements
@dani_agent
Twitter as a Communication
Channel and Foursquare as a
Location Provider
41.371141, 2.144209
41.378676, 2.153479
@dani_agent
• Streaming API offers 1% of the total Twitter
Traffic.
– We never get the Over-Exceed alarm.
• Is the sample good enough?
– YES!
Is the Twitter Streaming Sample
Good Enough?
@dani_agent
Area Knowledge@dani_agent
Social Importance
ME
Stranger
@dani_agent
How does it work?
@dani_agent
Scalability Issues
@dani_agent
MongoDB
• Why?
– Raw tweets from Streaming API: JSON
– Geospatial Index
– Scalability
• When?
– Crawlers Writting
– Tweets and venues access by the algorithm.
@dani_agent
OVER
3.000.000
geo-tweets
Neo4J
• Why?
– Social Graph Representation.
– Java Native
• When?
– Insert relationships
– Querying on social graph
@dani_agent
OVER 200.000
nodes
and 1.5M
relationships
So… how good is Cicerone?
@dani_agent
Pilot Experiment
One of the options is calculated by
Cicerone and the other one by
Foursquare. But only Cicerone knows
which is which. TELL US WHICH ONE
YOU LIKE BETTER.@dani_agent
Pilot Results
• 20 users – 150 requests
@dani_agent
Conclusions
• Pre-production Geo-Social Recommender
System.
• Spatial Capabilities and JSON by MongoDB
• Social Relationships by Neo4j.
• Good experimental results.
@dani_agent
@dani_agent
@dani_agent