The SUMMA Platform: A Scalable Infrastructure for Multi-lingual Multi-media Monitoring

Abstract

The open-source SUMMA Platform is a highly scalable distributed architecture for monitoring a large number of media broadcasts in parallel, with a lag behind actual broadcast time of at most a few minutes. The Platform offers a fully automated media ingestion pipeline capable of recording live broadcasts, detection and transcription of spoken content, translation of all text (original or transcribed) into English, recognition and linking of Named Entities, topic detection, clustering and crosslingual multi-document summarization of related media items, and last but not least, extraction and storage of factual claims in these news items. Browser-based graphical user interfaces provide humans with aggregated information as well as structured access to individual news items stored in the Platform's database. This paper describes the intended use cases and provides an overview over the system's implementation.

Multilingual Clustering of Streaming News

“…Finally, we discussed how to leverage different SVM training procedures for ranking and classification to improve monolingual and crosslingual clustering decisions. Our system is integrated in a larger media monitoring project (Liepins et al, 2017;Germann et al, 2018) and solving the usecases of monitors and journalists, having been validated with qualitative user testing.…”

Supporting Newsrooms with Journalistic Knowledge Graph Platforms: Current State and Future Directions

“…Journalists spend a lot of their time monitoring and filtering large volumes of news feeds like TV broadcasts, radio shows, social media and published news to keep them up-to-date, time that otherwise would have been invested in producing news [42]. Today's worldwide daily news volumes scale over 100,000 articles making it unfeasible for journalists to manually handle tasks like fact-checking and searching for related articles.…”

“…The internal users are news professionals like journalists who use JKPs for creating histories [35,39]; fact-checkers who conduct an essential task in combating with fake news and misinformation [17]; archivists who maintain up-to-date the schemas and news archives [14]; ICT professionals and knowledge engineers who develop and maintain JKPs [12]. Whereas, the external users are the audience [21]; the customers to whom new agencies offer services and researchers who investigate JKPs or use JKP to analyse data, as in the SUMMA project where "[political scientists want] to perform data analyses based on large amounts of news reports" [42] (p. 2).…”

“…. ] the British government" [42] (p. 1). JKPs also interact indirectly with the organisations responsible for controlling news media standards, vocabulary and ontologies (e.g., the IPTC organisation).…”

Processing Use Case Scenarios and Text in a Formal Style as Inputs for TFM-based Transformations

“…In recent years, analysis of informal and semiformal texts gained significant results using a deep learning approach. The open-source SUMMA platform (Germann et al, 2018) offers extraction and storage of factual claims from recorded live broadcast, spoken contents and text as well as storyline clustering and cluster summarization. The text is generated from semantic graphs produced by the parsing module.…”