2024-03-28T16:51:42Zhttps://www.tdx.cat/oai/requestoai:www.tdx.cat:10803/2836572024-03-15T10:58:07Zcom_10803_236col_10803_690279
nam a 5i 4500
Comportamiento del usuario
Modelado de usuario
Referrer
Navegación web
BrowseGraph
Recomendación
Clasificación
Datos implícitos
Objectos multimediales
User behavior
User modeling
Browsing
Recommender System
Ranking
Implicit feedback
Exploiting implicit user activity for media recommendation
[Barcelona] :
Universitat Pompeu Fabra,
2014
Accés lliure
http://hdl.handle.net/10803/283657
cr |||||||||||
AAMMDDs2014 sp ||||fsm||||0|| 0 eng|c
Trevisiol, Michele,
autor
Programa de doctorat en Tecnologies de la Informació i les Comunicacions,
degree
1 recurs en línia (193 pàgines)
Tesi
Doctorat
Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions
2014
Universitat Pompeu Fabra. Departament de Tecnologies de la Informació i les Comunicacions
Tesis i dissertacions electròniques
Baeza-Yates, Ricardo,
supervisor acadèmic
Jaimes Larrarte, Alejandro,
supervisor acadèmic
TDX
This thesis explores in depth how to use the user browsing behavior, and in particular the referrer URL, in order to understand the interest of the users. The aim is, first, to understand the preferences of the users from their navigation patterns, i.e., from the implicit actions of the users. Then, to exploit this information to personalize the content offered by the service provider. The key findings from our studies allowed us to propose different solutions in terms of recommender systems and ranking approaches for media items. We show how the browsing behavior of the users captured by the browsing logs is extremely meaningful to understand new users and to estimate their preferences.
f
ES-BaCBU
cat
rda
ES-BaCBU
text
txt
rdacontent
informàtic
c
rdamedia
recurs en línia
cr
rdacarrier