Performance of graph reconstruction method for large-scale web graph analysis

We have already proposed a graph analysis method that could shorten the analysis time by reconstructing a web graph. In our proposed method, a web graph is reconstructed for parallel distributed processing of possible graphs by clustering a web graph and reconstructing the web graph for Compression...

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Bibliographic Details
Published in2015 IEEE International Conference on Big Data (Big Data) pp. 2852 - 2854
Main Authors Takei, Ryota, Niimi, Ayahiko
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2015
Subjects
Algorithm design and analysis
Big data
Clustering algorithms
Data mining
Distributed processing
Electronic mail
Reconstruction algorithms
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Summary:We have already proposed a graph analysis method that could shorten the analysis time by reconstructing a web graph. In our proposed method, a web graph is reconstructed for parallel distributed processing of possible graphs by clustering a web graph and reconstructing the web graph for Compression Graph and Cluster Graphs. Compression Graph represents the relationship between clusters, whereas Cluster Graph contains nodes belonging to each cluster. When analyzing Compression Graph and Cluster Graphs, they can be processed in parallel because there is no relationship between Compression Graph and Cluster Graphs. Further examining our previous study in which we considered a small web graph, in the present paper, we discuss the performance of the proposed method on a large-scale web graph by experiments.
DOI:10.1109/BigData.2015.7364100