Signal: Advanced Real-Time Information Filtering

  • Miguel Martinez-Alvarez
  • Udo Kruschwitz
  • Wesley Hall
  • Massimo Poesio
Conference paper

DOI: 10.1007/978-3-319-16354-3_87

Volume 9022 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Martinez-Alvarez M., Kruschwitz U., Hall W., Poesio M. (2015) Signal: Advanced Real-Time Information Filtering. In: Hanbury A., Kazai G., Rauber A., Fuhr N. (eds) Advances in Information Retrieval. ECIR 2015. Lecture Notes in Computer Science, vol 9022. Springer, Cham

Abstract

The overload of textual information is an ever-growing problem to be addressed by modern information filtering systems, not least because strategic decisions are heavily influenced by the news of the world. In particular, business opportunities as well as threats can arise by using up-to-date information coming from disparate sources such as articles published by global news providers but equally those found in local newspapers or relevant blogposts. Common media monitoring approaches tend to rely on large-scale, manually created boolean queries. However, in order to be effective and flexible in a business environment, user information needs require complex, adaptive representations that go beyond simple keywords. This demonstration illustrates the approach to the problem that Signal takes: a cloud-based architecture that processes and analyses, in real-time, all the news of the world and allows its users to specify complex information requirements based on entities, topics, industry-specific terminology and keywords.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Miguel Martinez-Alvarez
    • 1
    • 2
  • Udo Kruschwitz
    • 2
  • Wesley Hall
    • 1
  • Massimo Poesio
    • 2
  1. 1.SignalLondonUK
  2. 2.University of EssexColchesterUK