Learning about Users from Observation

First Page		Document Content
Date: 2006-01-11 05:55:37 Information retrieval Knowledge representation Human–computer interaction Recommender system Natural language processing Information filtering system Personalization Machine learning User modeling Information science Science User interface techniques		Learning about Users from Observation Add to Reading List Source URL: aaai.org Download Document from Source Website File Size: 422,50 KB Share Document on Facebook

	Yum-Me: A Personalized Nutrient-Based Meal Recommender System LONGQI YANG, Cornell Tech, Cornell University CHENG-KANG HSIEH, University of California, Los Angeles HONGJIAN YANG and JOHN P. POLLAK, Cornell Tech, Cornell DocID: 1xVQo - View Document
	Yum-Me: A Personalized Nutrient-Based Meal Recommender System LONGQI YANG, Cornell Tech, Cornell University CHENG-KANG HSIEH, University of California, Los Angeles HONGJIAN YANG and JOHN P. POLLAK, Cornell Tech, Cornell DocID: 1tE3G - View Document
	Privacy Assessment of Data Flow Graphs for an Advanced Recommender System in the Smart Grid Fabian Knirsch1 , Dominik Engel1 , Cristian Neureiter1 , Marc Frincu2 , and Viktor Prasanna2 1 DocID: 1sXaB - View Document
	A Novel Recommender System in IoT Remo Manuel Frey1, Runhua Xu1, and Alexander Ilic2 I. ABSTRACT In Internet of Things (IoT), selling smart physical objects together with a compatible mobile app becomes an upcoming DocID: 1sIQs - View Document
	RiVal – A Toolkit to Foster Reproducibility in Recommender System Evaluation Alan Said Alejandro Bellogín DocID: 1sgiJ - View Document