It is becoming difficult to convey information from an everincreasing
number of digital sources to users in a condensed and meaningful
way. This growth has particularly occurred with peripheral information
sources. These ...
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 ...
In this work we propose that the high volumes of data on real-time networks like Twitter can be harnessed as a useful source of recommendation knowledge. We describe Buzzer, a news recommendation system that is capable of ...
User-generated content has dominated the web’s recent growth and today the so-called real-time web provides us with unprecedented access to the real-time opinions, views, and ratings of millions of users. For example, ...
Recommending news stories to users, based on their preferences,has long been a favourite domain for recommender systems research. In this paper, we describe a novel approach
to news recommendation that harnesses real-time ...
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