TONIC: Target Oriented Network Intelligence Collection for the social web

Roni Stern, Liron Samama, Rami Puzis, Tal Beja, Zahy Bnaya, Ariel Felner

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

In this paper we introduce the Target Oriented Network Intelligence Collection (TONIC) problem, which is the problem of finding profiles in a social network that contain information about a given target via automated crawling. We formalize TONIC as a search problem and a best-first approach is proposed for solving it. Several heuristics are presented to guide this search. These heuristics are based on the topology of the currently known part of the social network. The efficiency of the proposed heuristics and the effect of the graph topology on their performance is experimentally evaluated on the Google+ social network.

Original languageEnglish
Title of host publicationProceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013
Pages1184-1190
Number of pages7
StatePublished - 1 Dec 2013
Event27th AAAI Conference on Artificial Intelligence, AAAI 2013 - Bellevue, WA, United States
Duration: 14 Jul 201318 Jul 2013

Publication series

NameProceedings of the 27th AAAI Conference on Artificial Intelligence, AAAI 2013

Conference

Conference27th AAAI Conference on Artificial Intelligence, AAAI 2013
Country/TerritoryUnited States
CityBellevue, WA
Period14/07/1318/07/13

ASJC Scopus subject areas

  • Artificial Intelligence

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