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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 Semantically-oriented text planning for automatic summarization Casamayor, Gerard. - : Universitat Pompeu Fabra, 2021 In: TDX (Tesis Doctorals en Xarxa) (2021) BASE Show details 2 A Multimodal Analytics Platform for Journalists Analyzing Large-Scale, Heterogeneous Multilingual, and Multimedia Content Vrochidis, Stefanos; Moumtzidou, Anastasia; Gialampoukidis, Ilias... In: Front Robot AI (2018) BASE Show details 3 Using genre-specific features for patent summaries Codina Filbà, Joan; Bouayad-Agha, Nadjet; Burga Díaz, Alicia. - : Elsevier BASE Show details 4 Perspective-oriented generation of football match summaries: Old tasks, new challenges Bouayad-Agha, Nadjet; Casamayor, Gerard; Mille, Simon. - : ACM Association for Computer Machinery BASE Show details 5 MULTISENSOR: development of multimedia content integration technologies for journalism, media monitoring and international exporting decision support Vrochidis, Stefanos; Kompatsiaris, Ioannis; Casamayor, Gerard. - : Institute of Electrical and Electronics Engineers (IEEE) BASE Show details 6 A multimodal analytics platform for journalists analyzing large-scale, heterogeneous multilingual, and multimedia content Vrochidis, Stefanos; Moumtzidou, Anastasia; Gialampoukidis, Ilias; Liparas, Dimitris; Casamayor, Gerard; Wanner, Leo; Heise, Nicolaus; Wagner, Tilman; Bilous, Andriy; Jamin, Emmanuel; Simeonov, Boyan; Alexiev, Vladimir; Busch, Reinhard; Arapakis, Ioannis; Kompatsiaris, Ioannis. - : Frontiers Abstract: Analysts and journalists face the problem of having to deal with very large, heterogeneous, and multilingual data volumes that need to be analyzed, understood, and aggregated. Automated and simplified editorial and authoring process could significantly reduce time, labor, and costs. Therefore, there is a need for unified access to multilingual and multicultural news story material, beyond the level of a nation, ensuring context-aware, spatiotemporal, and semantic interpretation, correlating also and summarizing the interpreted material into a coherent gist. In this paper, we present a platform integrating multimodal analytics techniques, which are able to support journalists in handling large streams of real-time and diverse information. Specifically, the platform automatically crawls and indexes multilingual and multimedia information from heterogeneous resources. Textual information is automatically summarized and can be translated (on demand) into the language of the journalist. High-level information is extracted from both textual and multimedia content for fast inspection using concept clouds. The textual and multimedia content is semantically integrated and indexed using a common representation, to be accessible through a web-based search engine. The evaluation of the proposed platform was performed by several groups of journalists revealing satisfaction from the user side. ; This work was xsupported by the EC funded projects MULTISENSOR (FP7-610411) and V4Design (H2020-779962)x. Keyword: Big data; Journalism; Knowledge extraction; Multilingual content analysis; Multimodal analytics platform; Semantic analysis URL: http://hdl.handle.net/10230/47965 https://doi.org/10.3389/frobt.2018.00123 BASE Hide details

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