<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Starr, Brian</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Pazzani, Michael</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Do I Care?—Tell me what’s changed on the Web</style></title><secondary-title><style face="normal" font="default" size="100%">Proceedings of the AAAI Spring Symposium on Machine Learning in Information Access</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">agents</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">social search</style></keyword><keyword><style  face="normal" font="default" size="100%">World Wide Web</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">119-121</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;We describe the Do-I-Care agent, which uses machine learning to detect &quot;interesting&quot; changes to Web pages previously found to be relevant. Because this agent focuses on changes to known pages rather than discovering new pages, we increase the likelihood that the information found will be interesting. The agent’s accuracy in finding interesting changes and in learning is improved by exploiting regularities in how pages are changed. Additionally, these agents can be used collaboratively by cascading them and by propagating interesting findings to other users’ agents.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Starr, Brian</style></author><author><style face="normal" font="default" size="100%">Mark S. Ackerman</style></author><author><style face="normal" font="default" size="100%">Pazzani, Michael</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Do-I-Care: A Collaborative Web Agent</style></title><secondary-title><style face="normal" font="default" size="100%">Conference on Human Factors in Computing Systems (CHI&quot;96)</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">agents</style></keyword><keyword><style  face="normal" font="default" size="100%">collaboration</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise finding</style></keyword><keyword><style  face="normal" font="default" size="100%">expertise sharing</style></keyword><keyword><style  face="normal" font="default" size="100%">machine learning</style></keyword><keyword><style  face="normal" font="default" size="100%">social filtering</style></keyword><keyword><style  face="normal" font="default" size="100%">social search</style></keyword><keyword><style  face="normal" font="default" size="100%">World Wide Web</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">1996</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">Complete</style></url></web-urls></urls><pages><style face="normal" font="default" size="100%">v.2, 273–274</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Social filtering and collaborative resource discovery mechanisms often fail because of the extra burden, even tiny, placed on the user. This work proposes an innovative World Wide Web agent that uses a model of collaboration that leverages the natural incentives for individual users to easily provide for collaborative work.&lt;/p&gt;</style></abstract></record></records></xml>