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search.filters.applied.f.access: openAccess × Author: Ewerth, Ralph × DDC: 004 × DDC: 020 × Type: Text ×

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    Multimodal news analytics using measures of cross-modal entity and context consistency
    (London : Springer, 2021) Müller-Budack, Eric; Theiner, Jonas; Diering, Sebastian; Idahl, Maximilian; Hakimov, Sherzod; Ewerth, Ralph
    The World Wide Web has become a popular source to gather information and news. Multimodal information, e.g., supplement text with photographs, is typically used to convey the news more effectively or to attract attention. The photographs can be decorative, depict additional details, but might also contain misleading information. The quantification of the cross-modal consistency of entity representations can assist human assessors’ evaluation of the overall multimodal message. In some cases such measures might give hints to detect fake news, which is an increasingly important topic in today’s society. In this paper, we present a multimodal approach to quantify the entity coherence between image and text in real-world news. Named entity linking is applied to extract persons, locations, and events from news texts. Several measures are suggested to calculate the cross-modal similarity of the entities in text and photograph by exploiting state-of-the-art computer vision approaches. In contrast to previous work, our system automatically acquires example data from the Web and is applicable to real-world news. Moreover, an approach that quantifies contextual image-text relations is introduced. The feasibility is demonstrated on two datasets that cover different languages, topics, and domains.
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    B!SON: A Tool for Open Access Journal Recommendation
    (Heidelberg : Springer, 2022) Entrup, Elias; Eppelin, Anita; Ewerth, Ralph; Hartwig, Josephine; Tullney, Marco; Wohlgemuth, Michael; Hoppe, Anett; Nugent, Ronan
    Finding a suitable open access journal to publish scientific work is a complex task: Researchers have to navigate a constantly growing number of journals, institutional agreements with publishers, funders’ conditions and the risk of Predatory Publishers. To help with these challenges, we introduce a web-based journal recommendation system called B!SON. It is developed based on a systematic requirements analysis, built on open data, gives publisher-independent recommendations and works across domains. It suggests open access journals based on title, abstract and references provided by the user. The recommendation quality has been evaluated using a large test set of 10,000 articles. Development by two German scientific libraries ensures the longevity of the project.