PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Exploiting Surface Features for the Prediction of Podcast Preference
Manos Tsagias, Martha Larson and Maarten de Rijke
In: 31st European Conference on Information Retrieval Conference (ECIR 2009), 6-9 Apr 2009, Toulouse, France.


Podcasts display an unevenness characteristic of domains dominated by user generated content, resulting in potentially radical variation of the user preference they enjoy. We report on work that uses easily extractable surface features of podcasts in order to achieve solid performance on two podcast preference prediction tasks: classification of preferred vs. non-preferred podcasts and ranking podcasts by level of preference. We identify features with good discriminative potential by carrying out manual data analysis, resulting in a refinement of the indicators of an existent podcast preference framework. Our preference prediction is useful for topic-independent ranking of podcasts, and can be used to support download suggestion or collection browsing.

PDF - PASCAL Members only - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Information Retrieval & Textual Information Access
ID Code:6547
Deposited By:Christof Monz
Deposited On:08 March 2010