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Buzzer : online real-time topical news article and source recommender

Creator:

Phelan, Owen; McCarthy, Kevin; Smyth, Barry;

Institution: Springer
Subject Keywords: Recommender systems (Information filtering); Social media; Web personalization; User-generated content;
Region:
Description:

The significant growth of media and user-generated content online has allowed for the widespread adoption of recommender systems due to their proven ability to reduce the workload of a user and personalise
content. In this paper, we describe our prototype system called Buzzer, which harnesses real-time micro-blogging activity, such as Twitter, as the basis for promoting personalised content, such as news articles,
from RSS feeds. We also introduce several new features, that include a technique for recommending community articles from the pooled resources of all system users and also a mechanism for recommending source RSS feeds to which the user does not subscribe.

Format:

application/pdf

Related: http://dx.doi.org/10.1007/978-3-642-17080-5_27
Suggested citation:

Phelan, Owen; McCarthy, Kevin; Smyth, Barry; . () Buzzer : online real-time topical news article and source recommender [Online]. Available from: http://publichealthwell.ie/node/662860 [Accessed: 21st August 2019].

  

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