Cross-dependency inference in multi-layered networks: A collaborative filtering perspective

Chen Chen, Hanghang Tong, Lei Xie, Lei Ying, Qing He

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The increasingly connected world has catalyzed the fusion of networks from different domains, which facilitates the emergence of a new network model-multi-layered networks. Examples of such kind of network systems include critical infrastructure networks, biological systems, organization-level collaborations, crossplatform e-commerce, and so forth. One crucial structure that distances multi-layered network from other network models is its cross-layer dependency, which describes the associations between the nodes from different layers. Needless to say, the cross-layer dependency in the network plays an essential role in many data mining applications like system robustness analysis and complex network control. However, it remains a daunting task to know the exact dependency relationships due to noise, limited accessibility, and so forth. In this article, we tackle the cross-layer dependency inference problem by modeling it as a collective collaborative filtering problem. Based on this idea, we propose an effective algorithm FASCINATE that can reveal unobserved dependencies with linear complexity. Moreover, we derive FASCINATE-ZERO, an online variant of FASCINATE that can respond to a newly added node timely by checking its neighborhood dependencies. We perform extensive evaluations on real datasets to substantiate the superiority of our proposed approaches.

Original languageEnglish (US)
Article number3056562
JournalACM Transactions on Knowledge Discovery from Data
Volume11
Issue number4
DOIs
StatePublished - Jun 1 2017
Externally publishedYes

Fingerprint

Collaborative filtering
Critical infrastructures
Complex networks
Biological systems
Data mining
Fusion reactions

Keywords

  • Cross-layer dependency
  • Graph mining
  • Multi-layered network

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Cross-dependency inference in multi-layered networks : A collaborative filtering perspective. / Chen, Chen; Tong, Hanghang; Xie, Lei; Ying, Lei; He, Qing.

In: ACM Transactions on Knowledge Discovery from Data, Vol. 11, No. 4, 3056562, 01.06.2017.

Research output: Contribution to journalArticle

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