In this demo we present Flarty, a mobile location-based social network for the dynamic construction and recommendation of art routes in the city of Florence, Italy, via item based similarity algorithms, places topic extraction and user interest modeling. To achieve this goal Flarty derives knowledge from users check-ins and combines clustering techniques and recommendation algorithms, as well as features such as geolocation, to define groups of similar artworks or POIs (Points Of Interest) and to compute the most efficient routes likely to meet user’s interests. Model analysis takes into account ratings, topics extracted from textual features associated with the POIs, and users preferences computed exploiting collaborative filtering techniques on their past behavior.
Flarty: recommending art routes using check-ins latent topics / Alberto Del Bimbo; Andrea Ferracani; Daniele Pezzatini. - ELETTRONICO. - (2013), pp. 457-458. (Intervento presentato al convegno ACM Multimedia nel 2013) [10.1145/2502081.2502267].
Flarty: recommending art routes using check-ins latent topics
DEL BIMBO, ALBERTO;FERRACANI, ANDREA;PEZZATINI, DANIELE
2013
Abstract
In this demo we present Flarty, a mobile location-based social network for the dynamic construction and recommendation of art routes in the city of Florence, Italy, via item based similarity algorithms, places topic extraction and user interest modeling. To achieve this goal Flarty derives knowledge from users check-ins and combines clustering techniques and recommendation algorithms, as well as features such as geolocation, to define groups of similar artworks or POIs (Points Of Interest) and to compute the most efficient routes likely to meet user’s interests. Model analysis takes into account ratings, topics extracted from textual features associated with the POIs, and users preferences computed exploiting collaborative filtering techniques on their past behavior.I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.