Experiences with Complex User Profiles for Approximate P2P Community Matching (Contributo in atti di convegno)

Type
Label
  • Experiences with Complex User Profiles for Approximate P2P Community Matching (Contributo in atti di convegno) (literal)
Anno
  • 2011-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/CIT.2011.96 (literal)
Alternative label
  • Dazzi P., Mordacchini M., Baglini F. (2011)
    Experiences with Complex User Profiles for Approximate P2P Community Matching
    in 2011 IEEE 11th International Conference on Computer and Information Technology (CIT), Paphos, Cyprus, 31 Aug-02 Sept 2011
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Dazzi P., Mordacchini M., Baglini F. (literal)
Pagina inizio
  • 53 (literal)
Pagina fine
  • 58 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni
  • ID Modulo Commessa INT.P01.001.002 - 044 - Ubiquitous Internet Area di valutazione 01 - Scienze matematiche e informatiche (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
  • http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6036591 (literal)
Note
  • Scopu (literal)
  • PuMa (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR-ISTI, Pisa, Italy; CNR-IIT, Pisa, Italy; Università of Pisa, Italy (literal)
Titolo
  • Experiences with Complex User Profiles for Approximate P2P Community Matching (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 978-0-7695-4388-8 (literal)
Abstract
  • The problem of defining P2P overlays where peers characterized by similar interests are directly connected is currently an important research issue. We have recently proposed a two layer P2P architecture where the first layer exploits a gossip algorithm for the detection of communities of peers characterized by similar interests, while the second layer defines a DHT storing the profiles of the communities detected in the first layer. The DHT is exploited by peers joining the system to find out a community matching its interests. This paper investigates a DHT based approach supporting a similarity based search of user profiles. Our approach exploits Locality Sensitive Hashing to support the similarity indexing. The paper investigates several types of profiles to model user interests and evaluates the indexing mechanisms of the DHT with respect to the different types. Experimental evaluation has been conducted by considering a real data set. (literal)
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