Personalized news recommendation based on collaborative filtering

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We demonstrate the SciLens News Platform, a novel system for evaluating the quality of news articles. The SciLens News Platform automatically collects contextual information about news articles in real-time and provides quality indicators about their valid ...

This paper describes, develops, and validates SciLens, a method to evaluate the quality of scientific news articles. The starting point for our work are structured methodologies that define a series of quality aspects for manually evaluating news. Based on ...

Our modern society is struggling with an unprecedented amount of online misinformation, which does harm to democracy, economics, and cybersecurity. Journalism and politics have been impacted by misinformation on a global scale, with weakened public trust i ...

Personalization is pervasive in the online space as it leads to higher efficiency for the user and higher revenue for the platform by individualizing the most relevant content for each user. However, recent studies suggest that such personalization can lea ...

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News entities must select and filter the coverage they broadcast through their respective channels since the set of world events is too large to be treated exhaustively. The subjective nature of this filtering induces biases due to, among other things, res ...

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Social media is becoming more and more integrated in the distribution and consumption of news. How is news in social media different from mainstream news? % This paper presents a comparative analysis covering a span of 17 months and hundreds of news events ...

Early modern printed gazettes relied on a system of news exchange and text reuse largely based on handwritten sources. The reconstruction of this information exchange system is possible by detecting reused texts. We present a method to individuate text bor ...

The proliferation of online news creates a need for filtering interesting articles. Compared to other products, however, recommending news has specific challenges: news preferences are subject to trends, users do not want to see multiple articles with simi ...

We present WhatsUp, a collaborative filtering system for disseminating news items in a large-scale dynamic setting with no central authority. WhatsUp constructs an implicit social network based on user profiles that express the opinions of users about the ...

We present the Personalized News (PEN) recommender systems framework, currently in use by a newspaper website to evaluate various algorithms for news recommendations. We briefly describe its system architecture and related components. We show how a researc ...

We present the Personalized News (PEN) recommender systems framework, (Note that this paper is an extended abstract of Garcin2013b), currently in use by a newspaper website to evaluate various algorithms for news recommendations. We briefly describe its sy ...

Personalized news recommendation based on collaborative filtering

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