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Fast Text Based Classification of News Snippets for Telecom Assurance

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Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1602))

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Abstract

The quality of Telecom companies’ mobile service can be seriously compromised by the occurrence of different types of events, whether they are expected or not. The goal of this work is to automatically identify online news that report such events. Three possible topics are searched for: “fire”; “meteorologic” and “public gatherings”. Remaining news’ topics should be ignored. Each category was specifically chosen by its relevance towards the most known network providers’ problems. The data is highly unbalanced.

We compare different lightweight models for text classification using information collected from several Portuguese online newspapers: Support-Vector Machines (SVM), Fuzzy Fingerprints and K-Nearest Neighbours (KNN). More complex deep models, such as Bert or RoBerta, are dismissed due to the requirement of a fast response. The proposed models predict the categories based entirely on the title and the short news’ snippets that are freely available. Preliminary results indicate F1-scores above 0.78 for each of the three topics.

This work was supported by Fundação para a Ciência e a Tecnologia (FCT), through Portuguese national funds Ref. UIDB/50021/2020, Agência Nacional de Inovação (ANI), through the project CMU-PT MAIA Ref. 045909 and Inova-Ria associated with Altice Labs, S.A.

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Authors and Affiliations

  1. Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal

    Artur Simões & Joao Paulo Carvalho

  2. INESC-ID Lisboa, Lisbon, Portugal

    Artur Simões & Joao Paulo Carvalho

Authors
  1. Artur Simões
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  2. Joao Paulo Carvalho
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Corresponding author

Correspondence to Joao Paulo Carvalho .

Editor information

Editors and Affiliations

  1. University of Milano-Bicocca, Milan, Italy

    Davide Ciucci

  2. University of Oviedo, Oviedo, Spain

    Inés Couso

  3. University of Cádiz, Cádiz, Spain

    Jesús Medina

  4. University of Warsaw, Warsaw, Poland

    Dominik Ślęzak

  5. University of Perugia, Perugia, Italy

    Davide Petturiti

  6. Sorbonne Université, Paris, France

    Bernadette Bouchon-Meunier

  7. Iona College, New Rochelle, NY, USA

    Ronald R. Yager

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Simões, A., Carvalho, J.P. (2022). Fast Text Based Classification of News Snippets for Telecom Assurance. In: Ciucci, D., et al. Information Processing and Management of Uncertainty in Knowledge-Based Systems. IPMU 2022. Communications in Computer and Information Science, vol 1602. Springer, Cham. https://doi.org/10.1007/978-3-031-08974-9_6

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  • DOI: https://doi.org/10.1007/978-3-031-08974-9_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-08973-2

  • Online ISBN: 978-3-031-08974-9

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