Correlation Clustering Algorithm for Dynamic Complete Signed Graphs: An Index-based Approach

• URL: http://arxiv.org/abs/2301.00384v1
• Date: Sun, 1 Jan 2023 10:57:36 GMT
• Title: Correlation Clustering Algorithm for Dynamic Complete Signed Graphs: An Index-based Approach
• Authors: Ali Shakiba
• Abstract summary: In this paper, we reduce the complexity of approximating the correlation clustering problem from $O(mtimesleft( 2+ alpha (G) right)+n)$ to $O(m+n)$ for any given value of $varepsilon$ for a complete signed graph. Our approach gives the same output as the original algorithm and makes it possible to implement the algorithm in a full dynamic setting.
• Score: 9.13755431537592
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper, we reduce the complexity of approximating the correlation clustering problem from $O(m\times\left( 2+ \alpha (G) \right)+n)$ to $O(m+n)$ for any given value of $\varepsilon$ for a complete signed graph with $n$ vertices and $m$ positive edges where $\alpha(G)$ is the arboricity of the graph. Our approach gives the same output as the original algorithm and makes it possible to implement the algorithm in a full dynamic setting where edge sign flipping and vertex addition/removal are allowed. Constructing this index costs $O(m)$ memory and $O(m\times\alpha(G))$ time. We also studied the structural properties of the non-agreement measure used in the approximation algorithm. The theoretical results are accompanied by a full set of experiments concerning seven real-world graphs. These results shows superiority of our index-based algorithm to the non-index one by a decrease of %34 in time on average.

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