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TrAnET: Tracking and Analyzing the Evolution of Topics in Information Networks

  • Livio Bioglio
  • Ruggero G. PensaEmail author
  • Valentina Rho
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10536)

Abstract

This paper presents a system for tracking and analyzing the evolution and transformation of topics in an information network. The system consists of four main modules for pre-processing, adaptive topic modeling, network creation and temporal network analysis. The core module is built upon an adaptive topic modeling algorithm adopting a sliding time window technique that enables the discovery of groundbreaking ideas as those topics that evolve rapidly in the network.

Keywords

Information diffusion Topic modeling Citation networks 

Notes

Acknowledgments

This work is partially funded by project MIMOSA (MultIModal Ontology-driven query system for the heterogeneous data of a SmArtcity, “Progetto di Ateneo Torino_call2014_L2_157”, 2015–17).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of TurinTurinItaly

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