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Content Provider | ACM Digital Library |
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Author | Gülbahar, Mark Wenleder, Michael Scheuerer, Johannes Linnhoff-Popien, Claudia Erk, Alexander Weiß, Diana |
Abstract | With the steadily increasing amount of digital multimedia content, the user will be more and more overstrained. This applies to content being permanently available like videos of online video services as well as broadcast content like in the TV or radio domain. A promising solution for this problem is personalization. In the context of this paper, we refer to the selection and recommendation of content with respect to user's interests and preferences as personalization. These recommendations can either be presented to the user herself or be further used by services like a personalized electronic program guide (EPG) in the TV domain or for automated and personalized selection of content of online video services. This paper introduces an approach to personalize digital multimedia content based on user profile information. For this, two main mechanisms were developed: a profile generator that automatically creates user profiles representing the user preferences, and a content-based recommendation algorithm that estimates the user's interest in unknown content by matching her profile to metadata descriptions of the content. Both features are integrated into a personalization system. |
Starting Page | 281 |
Ending Page | 288 |
Page Count | 8 |
File Format | |
ISBN | 9781605582481 |
DOI | 10.1145/1413634.1413687 |
Language | English |
Publisher | Association for Computing Machinery (ACM) |
Publisher Date | 2008-09-10 |
Publisher Place | New York |
Access Restriction | Subscribed |
Subject Keyword | Multimedia Personalization Profiling Recommendation system |
Content Type | Text |
Resource Type | Article |
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