A Hybrid, Multi-dimensional Recommender for Journal Articles in a Scientific Digital Library

Autor:	Andre Vellino, David Zeber
Rok vydání:	2007
Zdroj:	2007 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology - Workshops.
DOI:	10.1109/wi-iatw.2007.29
Popis:	A recommender system for scientific scholarly articles that is both hybrid (content and collaborative filtering based) and multi-dimensional (across metadata categories such as subject hierarchies, journal clusters and keyphrases) can improve scientists' ability to discover new knowledge from a digital library. Providing users with an interface which enables the filtering of recommendations across these multiple dimensions can simultaneously provide explanations for the recommendations and increase the user's control over how the recommender behaves. 2007 IEEE/WIC/ACM International Conference on Web Intelligence and International Conference on Intelligent Agent Technology, Workshops, Silicon Valley, CA, USA, November 2-5, 2007
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::664110a868b4bbf19799005e9710ff7a https://doi.org/10.1109/wi-iatw.2007.29 Zobrazit plný text záznamu