Context-Aware Middleware for Anytime, Anywhere Social Networks Dario Bottazzi, Rebecca Montanari, and Alessandra Toninelli University of Bologna IEEE Intelligent.

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Presentation transcript:

Context-Aware Middleware for Anytime, Anywhere Social Networks Dario Bottazzi, Rebecca Montanari, and Alessandra Toninelli University of Bologna IEEE Intelligent Systems Volume 22, Issue 5 (September 2007) Year of Publication: 2007 Presentation by Sangkeun Lee, IDS Lab, SNU

Copyright  2008 by CEBT Introduction  Sociality characterizes an individual’s life  The web of social bindings is referred as a social network  Technology advances in wireless networks and the increasing diffusion of portable devices offer a chance to improve social- networking services The formation of ad hoc networks enables serendipitous social encounters between proximate users with common interest, anywhere and anytime Virtual spaces -> Physical spaces Group together people who are likely to share common characteristics and preferences 2

Copyright  2008 by CEBT Technical Challenges  Ubiquitous Environment More dynamic and heterogeneous than Internet-based Environment Set of potentially available social-network members varies, so it can’t be predetermined  What We need Location and proximity systems Expressive representation models of physical place and user characteristics Effective social-matching algorithm  SAMOA (Socially Aware and Mobile Architecture) Integrating a set of common management facilities for personalizing location-dependent social networks 3

Copyright  2008 by CEBT Emerging Requirements and Solution Guidelines  Current Solutions (location-centric social-computing) LoveGety, ProxyLady, SocialNet Proof-of-concept application protypes Built on top of the network layer Tend to provide dedicated support for specific application  Limitations Can rarely reuse ad hoc support in different application domains Must deal explicitly with all issues related to user and device mobility, intermittent connectivity, and availability 4

Copyright  2008 by CEBT The SAMOA Framework  A Middleware Solution Managing Social-network management details – Location detection and tracking – User profiling – Social matchmaking Let application developers focus on designing and developing the application – Accelerates application development – Reuse the same middleware-level support in different social-computing applications 5

Copyright  2008 by CEBT The SAMOA Framework  SAMOA lets mobile users create roaming social networks, following user movements, reflect at each instant all nearby encounters of interest  Context Visibility Place visibility (Place awareness) Profile visibility (Profile awareness)  Semantic matching algorithms Analyzing profiles and inferring potential semantic compatibility 6

Copyright  2008 by CEBT Social-Network Management Model  Managers The mobile ego users interested in creating social networks Responsible for defining the discovery scope boundaries  Clients Users located within the discovery scope boundaries Eligible to become members of the manager’s social network  Members Users affiliated with a social network 7

Copyright  2008 by CEBT 8

Metadata Model  SAMOA Entities Place, Users  Place Profile Identification Activity – (e.g. bookshop – shopping, reading)  User Profile Identification – identifier, user properties, age, gender, … Preference – Activities that the user is interested in-  Discovery Profile Desired Client attributes for each activity (e.g.A manager’s discovery profile state that he or she is looking for other users of the same age who are interested in the shopping activity, preferably in buying books) 9

Copyright  2008 by CEBT Social-Network Extraction Model  The place-dependent social network Shows only the members currently collocated with the network manager  The global social network Persistently records the whole set of place-dependent SN dynamically created over time  Two Semantic-Matching Algorithm 10

Copyright  2008 by CEBT 11

Copyright  2008 by CEBT Semantic-Matching Algorithm 12

Copyright  2008 by CEBT Semantic Matching Algorithm  Based on description-logic-based subsumption  Semantic Relationships in the activity or preference ontologies The user activity or preference can be – An instance of the activity or preference class in the activity or discovery profile (exact case) – An instance of a more generic activity or preference class (subsumes case) – An instance of a more specialized activity or preference class (plug-in case) 13

Copyright  2008 by CEBT SAMOA Middleware  A Layered Architecture  Built top on Java Virtual Machine  Message Transport Manager UDP-based point-to-point communication  Location/Proximity Manager Samoa entities advertise their online availability by broadcasting advertisement messages at regular times  Profile Manager  Semantic-Matching Engine  Place-Dependent Social-network Manager  Global Social-network Manager 14

Copyright  2008 by CEBT Viral-marketing Scenario  Social-network in a bookshop  Vendors forward promotional messages to customers in their bookshop & previously visited customers  Customer who receives a promotion can use SAMOA to forward the information to nearby customers (using customer’s place dependent social-network) or to all customers previously encountered in all visited bookshops 15

Copyright  2008 by CEBT Overview 16

Copyright  2008 by CEBT Review  Very Interesting Paper and A good topic to research Context-Aware + Social Network  Well-explained their concept The way of presenting their work is very good  Facebook or MySpace like commercial SNS + Context-Awareness may be a good research topic for a workshop paper  Privacy Issues  Maybe it’s just a context-aware application Which means that we do not have to use SAMOA rather than SOCAM, or CoBRA, or other so many Context-Aware Systems…. 17