Semantic Maps for Knowledge Management of Web and Social Information

  • Francesco Camastra
  • Angelo CiaramellaEmail author
  • Antonio Maratea
  • Le Hoang Son
  • Antonino Staiano
Part of the Studies in Computational Intelligence book series (SCI, volume 837)


We are deluged by a growing amount of data coming from heterogeneous sources, like web sites and social networks, and finding relevant information to extract potentially useful knowledge is becoming every day more challenging. The focus of this chapter is on describing techniques for knowledge representation and management of Web and social media data by semantic information modeling. Specifically, the following methods exploiting semantic information are described: (i) a method that provides a compact and structured representation of the concepts in a document (typically web pages) in form of graphs, ready for classification and agglomeration; (ii) a method to represent and synthesize the information content of Twitter conversations in the form of semantic maps, from which the main topics and orientation of tweeters may easily be read. From the obtained results, we observe that both methods provide promising performance.



This work was funded by the University of Naples “Parthenope” (project “Sostegno alla ricerca individuale per il triennio 2017–2019”).


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Francesco Camastra
    • 1
  • Angelo Ciaramella
    • 1
    Email author
  • Antonio Maratea
    • 1
  • Le Hoang Son
    • 2
  • Antonino Staiano
    • 1
  1. 1.Department of Science and TechnologiesUniversity of Naples “Parthenope”NaplesItaly
  2. 2.Vietnam National UniversityCau Giay, HanoiVietnam

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