Latent interest-group discovery and management by peer-to-peer online social networks

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

We address management of latent, emerging interest groups (IGs), spanning both unsupervised, distributed IG discovery and anycast-query forwarding, in dynamic peer-to-peer (P2P) on-line social networks. The P2P network has at least one layer of super-peers (Diaspora pods) that support a group of ordinary peers/clients. There are a number of challenges here, including: i) semantic processing at scale to disambiguate word meanings in queries; ii) unsupervised estimation of the number of active IGs; iii) detection of IG churn and emergent IGs; iv) design of optimal query forwarding to maximize query resolution and minimize the required number of hops, while achieving practical local cache searching and network communications. In this preliminary study, we assume a common, fixed keyword lexicon for query formation and latent IG characterization. We propose unsupervised, dynamic, on-line clustering that mines the super-peers' query caches in a distributed fashion. Customized Bayesian Information Criterion based model-order selection is employed, independently by each super-peer, to estimate the set of active IGs and to help achieve efficient query forwarding. The proposed method is numerically evaluated against both exhaustive cache search and a random walk strategy.

Original languageEnglish (US)
Title of host publicationProceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013
Pages162-167
Number of pages6
DOIs
StatePublished - Dec 1 2013
Event2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013 - Washington, DC, United States
Duration: Sep 8 2013Sep 14 2013

Publication series

NameProceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013

Other

Other2013 ASE/IEEE Int. Conf. on Social Computing, SocialCom 2013, the 2013 ASE/IEEE Int. Conf. on Big Data, BigData 2013, the 2013 Int. Conf. on Economic Computing, EconCom 2013, the 2013 PASSAT 2013, and the 2013 ASE/IEEE Int. Conf. on BioMedCom 2013
CountryUnited States
CityWashington, DC
Period9/8/139/14/13

All Science Journal Classification (ASJC) codes

  • Software

Fingerprint Dive into the research topics of 'Latent interest-group discovery and management by peer-to-peer online social networks'. Together they form a unique fingerprint.

  • Cite this

    He, J., Miller, D. J., & Kesidis, G. (2013). Latent interest-group discovery and management by peer-to-peer online social networks. In Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013 (pp. 162-167). [6693328] (Proceedings - SocialCom/PASSAT/BigData/EconCom/BioMedCom 2013). https://doi.org/10.1109/SocialCom.2013.31