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I LINK :Search and Routing in Social Networks

I LINK :Search and Routing in Social Networks. Presenter : Chun-Ping Wu Authors :Jeffrey Davcitz , Jiye Yu, Sugato Basu , David Gutelius , Alexandra Harris. 國立雲林科技大學 National Yunlin University of Science and Technology. KDD 2007. Outline. Motivation Objective ILINK FAQTORY

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I LINK :Search and Routing in Social Networks

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  1. ILINK:Search and Routing in Social Networks Presenter : Chun-Ping Wu Authors :Jeffrey Davcitz, Jiye Yu, SugatoBasu, David Gutelius, Alexandra Harris 國立雲林科技大學 National Yunlin University of Science and Technology KDD 2007

  2. Outline • Motivation • Objective • ILINK • FAQTORY • Learning Framework • Case Study • Conclusion • Comments

  3. Motivation • This paper focuses on the problem of modeling how social networks accomplish tasks through peer production style collaboration.

  4. Objective • To propose a general interaction model for the underlying social networks and then a specific model(ILINK) for social search and message routing.

  5. ILINK • The ILINK model has various components. • Node • Each node represents a user in the network, and has an associated profile. • Supernode • A database D storing all the past message streams. • Profile parameters E, R, F for all the nodes in the network. • The set of all possible topics T. • Message • A message m is routed between a node and the supernode.

  6. FAQTORY • FAQtory system is implemented as a three-tiered client-server application. • The client/front tier facilitates interactions between the nodes and the FAQtory server via APIs. • Web browser • Email clients • Instant messenger

  7. FAQTORY-Routing Mechanism

  8. Learning Framework • The learning framework in this case has to solve a set of interrelated learning problems. • Heterogeneous topics • Cold-start problem • Privacy issues • Prior knowledge • Message matching • Scalability • Incremental learning

  9. Case Study and Applications • Calo Test Pilot • The FAQtory system of ILINKwas developed as part of CALO, an adaptive cognitive system funded under DARPA’s PAL(Perceptive Assistant that Learns) program. • PatoonLeader • Provided with two features that leverage ILINKtechnology: “Suggested Discussions” and the “Moderator’s Assistant”. • Other Message Applications • Smart Rss Filter • Message Routing for Advertising

  10. Conclusion • The web has made large peer production frameworks possible, which are unprecedented in terms of both scale and intensity. • The importance of making such models work for real, ongoing web-based collaboration efforts is a growing issue and a wonderful challenge for machine learning and data mining techniques. 10

  11. Comments • Advantage • The idea is good. • Drawback • Many practical and theoretical issues remain. • Application • Peer production 11

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