| dc.creator | Corbellini, Alejandro | |
| dc.creator | Ríos, Carlos | |
| dc.creator | Godoy, Daniela Lis | |
| dc.creator | Schiaffino, Silvia | |
| dc.date | 2018-09 | |
| dc.date | 2018-11-20T12:13:48Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/70805 | |
| dc.identifier | http://47jaiio.sadio.org.ar/sites/default/files/ASAI-19.pdf | |
| dc.identifier | issn:2451-7585 | |
| dc.description | The pervasiveness of geo-located devices has opened new possibilities in recommender systems on social networks. In effect, Location-Based Social Networks or LBSNs are a relatively new breed of social networks that let users share their location by triggering ”check-in” events on venues, such as businesses or historical places. In this paper, we compare the performance of traditional rating and social-based similarity metrics against location-based metrics in a userbased collaborative filtering algorithm that recommends venues or places to visit.
This analysis was performed on a large real-world dataset provided by the Yelp social network service. Our results show that, geo-located metrics perform as well as rating or social metrics for selecting like-minded users and, thus, to issue a recommendation. | |
| dc.description | Sociedad Argentina de Informática e Investigación Operativa | |
| dc.format | application/pdf | |
| dc.language | en | |
| dc.rights | http://creativecommons.org/licenses/by-sa/3.0/ | |
| dc.rights | Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) | |
| dc.subject | Ciencias Informáticas | |
| dc.subject | geo-located devices | |
| dc.subject | social networks | |
| dc.title | An analysis on the impact of geolocation in recommending venues in location-based social networks | |
| dc.type | Objeto de conferencia | |
| dc.type | Objeto de conferencia | |
