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International Conference on Complex Networks and their Applications

COMPLEX NETWORKS 2018: Complex Networks and Their Applications VII pp 158–168Cite as

Exploring Partially Observed Networks with Nonparametric Bandits

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 813))

Abstract

Real-world networks such as social and communication networks are too large to be observed entirely. Such networks are often partially observed such that network size, network topology, and nodes of the original network are unknown. In this paper we formalize the Adaptive Graph Exploring problem. We assume that we are given an incomplete snapshot of a large network and additional nodes can be discovered by querying nodes in the currently observed network. The goal of this problem is to maximize the number of observed nodes within a given query budget. Querying which set of nodes maximizes the size of the observed network? We formulate this problem as an exploration-exploitation problem and propose iKNN-UCB, a novel nonparametric multi-arm bandit (MAB) algorithm for determining which nodes to be queried in an adaptive manner. Using synthetic networks and real-world networks from different domains, we demonstrate that our proposed algorithm discovers up to 40% more nodes compared to existing state-of-the-art algorithms.

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Notes

  1. 1.

    Source code available at https://bitbucket.org/kau_mad/bandits/src.

  2. 2.

    http://snap.stanford.edu/data/index.html.

  3. 3.

    https://dev.twitter.com/rest/reference/get/followers/ids.

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Acknowledgement

This work was supported by JSPS Grant-in-Aid for Scientific Research(B) (Grant Number 17H01785) and JST CREST (Grant Number JPMJCR1687).

Author information

Authors and Affiliations

  1. Tokyo Institute of Technology, W8-59, 2-12-1, Ookayama, Meguro-ku, Tokyo, 152-8552, Japan

    Kaushalya Madhawa & Tsuyoshi Murata

Authors
  1. Kaushalya Madhawa
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  2. Tsuyoshi Murata
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Corresponding author

Correspondence to Kaushalya Madhawa .

Editor information

Editors and Affiliations

  1. Nokia Bell Labs, Cambridge, UK

    Luca Maria Aiello

  2. IUT Lumière, University of Lyon, Bron Cedex, France

    Chantal Cherifi

  3. LE2I UMR CNRS 6306 9, University of Burgundy, Dijon Cedex, France

    Hocine Cherifi

  4. Mathematical Institute, University of Oxford, Oxford, UK

    Renaud Lambiotte

  5. Department of Computer Science and Technology, The Computer Laboratory, University of Cambridge, Cambridge, UK

    Pietro Lió

  6. Center for Complex Networks and Systems Research, School of Informatics, Computing, and Engineering, Indiana University, Bloomington, IN, USA

    Luis M. Rocha

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Madhawa, K., Murata, T. (2019). Exploring Partially Observed Networks with Nonparametric Bandits. In: Aiello, L., Cherifi, C., Cherifi, H., Lambiotte, R., Lió, P., Rocha, L. (eds) Complex Networks and Their Applications VII. COMPLEX NETWORKS 2018. Studies in Computational Intelligence, vol 813. Springer, Cham. https://doi.org/10.1007/978-3-030-05414-4_13

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