Publication

PEN recsys: a Personalized News Recommender Systems Framework (DEMO)

Boi Faltings, Florent Frédéric Garcin
2013
Conference Papers

Abstract

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 system architecture and related components. We show how a researcher can easily evaluate different algorithms thanks to a web-based interface.

Official source

https://infoscience.epfl.ch/entities/publication/525ba6b6-2537-4669-a722-fb75dddc98d5

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Boi Faltings, Florent Frédéric Garcin
2013
Conference Papers

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/525ba6b6-2537-4669-a722-fb75dddc98d5

About this result

Related concepts (16)

Recommender system

A recommender system, or a recommendation system (sometimes replacing 'system' with a synonym such as platform or engine), is a subclass of information filtering system that provide suggestions for items that are most pertinent to a particular user. Typically, the suggestions refer to various decision-making processes, such as what product to purchase, what music to listen to, or what online news to read. Recommender systems are particularly useful when an individual needs to choose an item from a potentially overwhelming number of items that a service may offer.

Personalization

Personalization (broadly known as customization) consists of tailoring a service or a product to accommodate specific individuals, sometimes tied to groups or segments of individuals. A wide variety of organizations use personalization to improve customer satisfaction, digital sales conversion, marketing results, branding, and improved website metrics as well as for advertising. Personalization is a key element in social media and recommender systems. Personalization is affecting every sector of society—work, leisure, and citizenship.

Personalized marketing

Personalized marketing, also known as one-to-one marketing or individual marketing, is a marketing strategy by which companies leverage data analysis and digital technology to deliver individualized messages and product offerings to current or prospective customers. Advancements in data collection methods, analytics, digital electronics, and digital economics, have enabled marketers to deploy more effective real-time and prolonged customer experience personalization tactics.

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Multi-Step Critiquing User Interface for Recommender Systems

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Recommendations with personalized explanations have been shown to increase user trust and perceived quality and help users make better decisions. Moreover, such explanations allow users to provide feedback by critiquing them. Several algorithms for recomme ...

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Unified and Scalable Incremental Recommenders with Consumed Item Packs

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