Heterogeneous Graphlets
Ryan A. Rossi, Nesreen K. Ahmed, Aldo Carranza, David Arbour, Anup, Rao, Sungchul Kim, Eunyee Koh

TL;DR
This paper introduces typed graphlets, a generalization of graphlets for heterogeneous networks, along with efficient algorithms for counting them, enabling faster analysis of complex networks.
Contribution
The paper proposes a novel framework for counting typed graphlets in heterogeneous networks with algorithms that are faster and more space-efficient than existing methods for simpler graphlet notions.
Findings
Algorithms achieve exact counts in o(1) time per edge.
Proposed methods are orders of magnitude faster than previous approaches.
Efficient parallel implementation enables analysis of large networks.
Abstract
In this paper, we introduce a generalization of graphlets to heterogeneous networks called typed graphlets. Informally, typed graphlets are small typed induced subgraphs. Typed graphlets generalize graphlets to rich heterogeneous networks as they explicitly capture the higher-order typed connectivity patterns in such networks. To address this problem, we describe a general framework for counting the occurrences of such typed graphlets. The proposed algorithms leverage a number of combinatorial relationships for different typed graphlets. For each edge, we count a few typed graphlets, and with these counts along with the combinatorial relationships, we obtain the exact counts of the other typed graphlets in o(1) constant time. Notably, the worst-case time complexity of the proposed approach matches the time complexity of the best known untyped algorithm. In addition, the approach lends…
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