@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