Please use this identifier to cite or link to this item:
Title: Long term goal oriented recommender systems
Authors: AmirHossein Nabizadeh
Alípio Jorge
José Paulo Leal
Issue Date: 2015
Abstract: The main goal of recommender systems is to assist users in finding items of their interest in very large collections. The use of good automatic recommendation promotes customer loyalty and user satisfaction because it helps users to attain their goals. Current methods focus on the immediate value of recommendations and are evaluated as such. This is insufficient for long term goals, either defined by users or by platform managers. This is of interest in recommending learning resources to learn a target concept, and also when a company is organizing a campaign to lead users to buy certain products or moving to a different customer segment. Therefore, we believe that it would be useful to develop recommendation algorithms that promote the goals of users and platform managers (e.g. e-shop manager, e-learning tutor, ministry of culture promotor). Accordingly, we must define appropriate evaluation methodologies and demonstrate the concept on practical cases.
metadata.dc.type: conferenceObject
Appears in Collections:CRACS - Articles in International Conferences
LIAAD - Articles in International Conferences

Files in This Item:
File Description SizeFormat 
P-00G-SXJ.pdf746.56 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.