Making your interests follow you on twitter (Contributo in atti di convegno)

Type
Label
  • Making your interests follow you on twitter (Contributo in atti di convegno) (literal)
Anno
  • 2012-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1145/2396761.2396786 (literal)
Alternative label
  • Pennacchiotti M., Silvestri F., Vahabi H., Venturini R. (2012)
    Making your interests follow you on twitter
    in The 21st ACM International Conference on Information and Knowledge Management, Maui, Hawaii, USA, October 29-November 2 2012
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Pennacchiotti M., Silvestri F., Vahabi H., Venturini R. (literal)
Pagina inizio
  • 165 (literal)
Pagina fine
  • 174 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • convegno ISI (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://dl.acm.org/citation.cfm?id=2396786 (literal)
Note
  • Scopu (literal)
  • PuMa (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • eBay Research Inc., San Jose, US; CNR-ISTI, Pisa, Italy; CNR-ISTI, Pisa, Italy; omputer Science Department, University of Pisa, Italy; (literal)
Titolo
  • Making your interests follow you on twitter (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-1-4503-1156-4 (literal)
Abstract
  • In this paper we introduce the task of tweet recommenda- tion, the problem of suggesting tweets that match a user's interests and likes. We propose an Information-Retrieval- like model that leverages the content of the user's tweets and those of her friends, and that effectively retrieves a set of tweets that is personalized and varied in nature. Our approach could be easily leveraged to build, for example, a Twitter or Facebook timeline that collects messages that are of interest for the user, but that are not posted by her friends. We compare to typical approaches used in similar tasks, reporting significant gains in terms of overall preci- sion, up to about +20%, on both a corpus-based evaluation and real world user study. (literal)
Prodotto di
Autore CNR
Insieme di parole chiave

Incoming links:


Prodotto
Autore CNR di
Insieme di parole chiave di
data.CNR.it