Acquiring Case Adaptation Knowledge from Humans, Learning, and the Web

old_uid5581
titleAcquiring Case Adaptation Knowledge from Humans, Learning, and the Web
start_date2008/11/13
schedule14h-17h
onlineno
summaryHow to acquire case adaptation knowledge is a classic problem for case-based reasoning. This talk presents ongoing research on applying an incremental human-centered approach to adaptation learning. The work brings together human interaction, machine learning, ``just-in-time'' knowledge mining from Web sources, and learned personalization to increase the CBR system's ability to serve the needs of individual users. The talk illustrates encouraging initial results and highlights some open challenges.
responsiblesCordier