Exploiting Statistical & Relational Information on the Web and in Social Media

 

Tutorial at SDM-11 in Mesa, Arizona

April 30, 2011

Time: 8:30am

Room: Kiva C


Presenters: Lise Getoor & Lily Mihalkova

Description: The popularity of Web 2.0, characterized by a proliferation of social media sites, and Web 3.0, with more richly semantically annotated objects and relationships, brings to light a variety of important prediction, ranking, and extraction tasks. The input to these tasks is often best seen as a (noisy) multi-relational graph, such as the graph of the Web itself; the click graph, defined by user interactions with Web sites; and the social graph, defined by friendships and affiliations on social media sites.


The first part of this tutorial will describe several common Web applications and will focus on their shared abstractions, showing how they can be cast as reasoning over multi-relational graphs. The second part of the tutorial will describe statistical relational learning (SRL) techniques, arguing in favor of the use of SRL as a unifying framework for learning and reasoning with multi-relational information on the Web, and will describe in detail several Web applications of SRL.

We expect that our audience will walk away with an appreciation for the diversity of Web applications naturally modeled as graphs, and with sufficient knowledge of available SRL tools to start exploring Web applications.


Tutorial materials