FH
Frank Hopfgartner
Authored
20 records found
CLEF NewsREEL 2017 Overview
Offline and Online Evaluation of Stream-based News Recommender Systems
The CLEF NewsREEL challenge allows researchers to evaluate news recommendation algorithms both online (NewsREEL Live) and offline (News-REEL Replay). Compared with the previous year NewsREEL challenged participants with a higher volume of messages and new news portals. In the 201
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CLEF NewsREEL 2016
Comparing Multi-Dimensional Offline and Online Evaluation of News Recommender Systems
Running in its third year at CLEF, NewsREEL challenged participantsto develop news recommendation algorithms and have them benchmarked inan online (Task 1) and offline setting (Task 2), respectively. This paper providesan overview of the NewsREEL scenario, outlines this year’s ca
...
CLEF NewsREEL 2016
Comparing Multi-Dimensional Offline and Online Evaluation of News Recommender Systems
Running in its third year at CLEF, NewsREEL challenged participantsto develop news recommendation algorithms and have them benchmarked inan online (Task 1) and offline setting (Task 2), respectively. This paper providesan overview of the NewsREEL scenario, outlines this year’s ca
...
CLEF NewsREEL 2016
Comparing Multi-Dimensional Offline and Online Evaluation of News Recommender Systems
Running in its third year at CLEF, NewsREEL challenged participantsto develop news recommendation algorithms and have them benchmarked inan online (Task 1) and offline setting (Task 2), respectively. This paper providesan overview of the NewsREEL scenario, outlines this year’s ca
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
Overview of newsreel’16
Multi-dimensional evaluation of real-time stream-recommendation algorithms
Successful news recommendation requires facing the challenges of dynamic item sets, contextual item relevance, and of fulfilling non-functional requirements, such as response time. The CLEF NewsREEL challenge is a campaign-style evaluation lab allowing participants to tackle news
...
CLEF NewsREEL 2017 Overview
A Stream-Based Recommender Task for Evaluation and Education
News recommender systems provide users with access to news stories that they find interesting and relevant. As other online, stream-based recommender systems, they face particular challenges, including limited information on users’ preferences and also rapidly fluctuating item co
...
CLEF NewsREEL 2017 Overview
A Stream-Based Recommender Task for Evaluation and Education
News recommender systems provide users with access to news stories that they find interesting and relevant. As other online, stream-based recommender systems, they face particular challenges, including limited information on users’ preferences and also rapidly fluctuating item co
...
CLEF NewsREEL 2017 Overview
A Stream-Based Recommender Task for Evaluation and Education
News recommender systems provide users with access to news stories that they find interesting and relevant. As other online, stream-based recommender systems, they face particular challenges, including limited information on users’ preferences and also rapidly fluctuating item co
...
CLEF NewsREEL 2017 Overview
A Stream-Based Recommender Task for Evaluation and Education
News recommender systems provide users with access to news stories that they find interesting and relevant. As other online, stream-based recommender systems, they face particular challenges, including limited information on users’ preferences and also rapidly fluctuating item co
...
CLEF NewsREEL 2017 Overview
A Stream-Based Recommender Task for Evaluation and Education
News recommender systems provide users with access to news stories that they find interesting and relevant. As other online, stream-based recommender systems, they face particular challenges, including limited information on users’ preferences and also rapidly fluctuating item co
...
Idomaar
A Framework for Multi-dimensional Benchmarking of Recommender Algorithms
In real-world scenarios, recommenders face non-functional requirementsof technical nature and must handle dynamic data in the formof sequential streams. Evaluation of recommender systems musttake these issues into account in order to be maximally informative.In this paper, we pre
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