Date: Wednesday, 08 October 2008, 6:30 PM
Location: Hewlett Packard (see directions), Pruneridge and Wolfe, Cupertino, Bldg. 48, Oak Room.
Cost: Free and open to all who wish to attend, but membership is
only $10/year.
Topic
Online information services have grown too large for users to navigate without the help of automated tools (i.e. collaborative filtering), which makes recommendations to users based on their collective past behavior. While many similarity measures have been proposed and individually evaluated, they have not been evaluated relative to each other in a large real-world environment. We present an extensive empirical comparison of six distinct measures of similarity for recommending online communities to members of the Orkut social network. We determine the usefulness of the different recommendations by actually measuring users' propensity to visit and join recommended communities. We also examine how the ordering of recommendations influenced user selection, as well as interesting social issues that arise in recommending communities within a real social network.
About the Speaker
Ellen Spertus is a research scientist at Google, where she works on social networks, and an associate professor of computer science at Mills College (on leave). She received her bachelor's, master's, and doctoral degrees in computer science from MIT and has done research in computer architecture, Internet search, and online communications and community.