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  1. Proceedings of the 3rd international workshop on Automated information extraction in media production (AIEMPro '10)
  2. Automatic news recommendations via profiling
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Technologies for next-generation multi-media libraries: the contentus project
Narrative theme navigation for sitcoms supported by fan-generated scripts
Towards automatic speaker retrieval for large multimedia archives
Implicit news recommendation based on user interest models and multimodal content analysis
Generic architecture for event detection in broadcast sports video
A novel video thumbnail extraction method using spatiotemporal vector quantization
Content-based video genre classification using multiple cues
Unsupervised event segmentation of news content with multimodal cues
Shiatsu: semantic-based hierarchical automatic tagging of videos by segmentation using cuts
Role-based identity recognition for telecasts
Automatic news recommendations via profiling
Efficient video breakup detection and verification

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Automatic news recommendations via profiling

Content Provider ACM Digital Library
Author Van de Walle, Rik Mannens, Erik Van Deursen, Davy Coppens, Sam Dacquin, Hendrik De Pessemier, Toon
Abstract Today, people have only limited, valuable leisure time at their hands which they want to fill in as good as possible according to their own interests, whereas broadcasters want to produce and distribute news items as fast and targeted as possible. These (developing) news stories can be characterised as dynamic, chained, and distributed events in addition to which it is important to aggregate, link, enrich, recommend, and distribute these news event items as targeted as possible to the individual, interested user. In this paper, we show how personalised recommendation and distribution of news events, described using an RDF/OWL representation of the NewsML-G2 standard, can be enabled by automatically categorising and enriching news events metadata via smart indexing and linked open datasets available on the web of data. The recommendations - based on a global, aggregated profile, which also takes into account the (dis)likings of peer friends - are finally fed to the user via a personalised RSS feed. As such, the ultimate goal is to provide an open, user-friendly recommendation platform that harnesses the end-user with a tool to access useful news event information that goes beyond basic information retrieval. At the same time, we provide the (inter)national community with standardised mechanisms to describe/distribute news event and profile information.
Starting Page 45
Ending Page 50
Page Count 6
File Format PDF
ISBN 9781450301640
DOI 10.1145/1877850.1877863
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2010-10-29
Publisher Place New York
Access Restriction Subscribed
Subject Keyword Profiling News modelling Recommendation
Content Type Text
Resource Type Article
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