Author: Andreas Lommatzsch
Images play an important role in online news articles and news consumption patterns. The influence of images on the perceived relevance of news items as well as the factors making images interesting in news are not well researched yet. This has been the motivation for us to setup the "News Images" task in the Multi-MediaEval Benchmark.
The "News Images" task aims to achieve additional insight about the role of images in news articles. The task supplies a large set of articles (including text body, and headlines) and the accompanying images. The task requires participants to predict which image was used to accompany each article and also predict frequently clicked articles on the basis of accompanying images.
In the challenge training data describing the news and the interest in the news items (number of views, number of clicks, CTR) are provided. The performance of the developed algorithms is benchmarked based on the data of a subsequent month. The reassignment of images to news items is measured based on the accuracy (percentage of correctly assigned images); the performance of the relevance prediction is measured based on the Precision@N (the top N entries should be predicted correctly).
The registration is now open for participants. The MediaEval conference will be held in December 2020. Due to COVID-19 this year MediaEval goes fully virtually online. Thus, participants can save time and money usually needed for traveling. So there is more time for developing new algorithms, building interesting presentations and the preparing good discussions. More details about the MediaEval benchmark can be found on the official web page.
The MediaEval2020 Webpage
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