Analysis of Text-Enriched Heterogeneous Information Networks

  • Jan KraljEmail author
  • Anita Valmarska
  • Miha Grčar
  • Marko Robnik-Šikonja
  • Nada Lavrač
Part of the Studies in Big Data book series (SBD, volume 16)


This chapter addresses the analysis of information networks, focusing on heterogeneous information networks with more than one type of nodes and arcs. After an overview of tasks and approaches to mining heterogeneous information networks, the presentation focuses on text-enriched heterogeneous information networks whose distinguishing property is that certain nodes are enriched with text information. A particular approach to mining text-enriched heterogeneous information networks is presented that combines text mining and network mining approaches. The approach decomposes a heterogeneous network into separate homogeneous networks, followed by concatenating the structural context vectors calculated from separate homogeneous networks with the bag-of-words vectors obtained from textual information contained in certain network nodes. The approach is show-cased on the analysis of two real-life text-enriched heterogeneous citation networks.


Heterogeneous Information Networks Homogeneous Network Minimum Term Frequency Link Prediction Page Rank 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The presented work was partially supported by the European Commission through the Human Brain Project (Grant number 604102) and by the Slovenian Research Agency project “Development and applications of new semantic data mining methods in life sciences” (Grant number J2-5478).


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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Jan Kralj
    • 1
    • 2
    Email author
  • Anita Valmarska
    • 1
    • 2
  • Miha Grčar
    • 3
  • Marko Robnik-Šikonja
    • 3
  • Nada Lavrač
    • 1
    • 2
    • 4
  1. 1.Jožef Stefan InstituteLjubljanaSlovenia
  2. 2.Jožef Stefan International Postgraduate SchoolLjubljanaSlovenia
  3. 3.Faculty of Computer and Information ScienceLjubljanaSlovenia
  4. 4.University of Nova GoricaNova GoricaSlovenia

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