Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/2360
Title: TV Recommendation and Personalization Systems: integrating broadcast and video on-demand services
Authors: Paula Viana
Márcio Micael Soares
Issue Date: 2012
Abstract: The expansion of Digital Television and the convergence between conventional broadcasting and television over IP contributed to the gradual increase of the number of available channels and on demand video content. Moreover, the dissemination of the use of mobile devices like laptops, smartphones and tablets on everyday activities resulted in a shift of the traditional television viewing paradigm from the couch to everywhere, anytime from any device. Although this new scenario enables a great improvement in viewing experiences, it also brings new challenges given the overload of information that the viewer faces. Recommendation systems stand out as a possible solution to help a watcher on the selection of the content that best fits his/her preferences. This paper describes a web based system that helps the user navigating on broadcasted and online television content by implementing recommendations based on collaborative and content based filtering. The algorithms developed estimate the similarity between items and users and predict the rating that a user would assign to a particular item (television program, movie, etc.). To enable interoperability between different systems, programs' characteristics (title, genre, actors, etc.) are stored according to the TV-Anytime standard. The set of recommendations produced are presented through a Web Application that allows the user to interact with the system based on the obtained recommendations. © 2014 AECE.
URI: http://repositorio.inesctec.pt/handle/123456789/2360
http://dx.doi.org/10.4316/AECE
metadata.dc.type: conferenceObject
Publication
Appears in Collections:CTM - Articles in International Journals

Files in This Item:
File Description SizeFormat 
PS-07489.pdf519.89 kBAdobe PDFView/Open


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