Mining Interesting Itemsets in Graph Datasets

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Provided by: University of Anbar
Topic: Big Data
Format: PDF
Traditionally, pattern discovery in graphs has been mostly limited to searching for frequent subgraphs, reoccurring patterns within which nodes with certain labels are frequently interconnected in exactly the same way. The authors relax this requirement by claiming that a set of labels is interesting if they often occur in each other's vicinity, but not necessarily always interconnected by exactly the same structures. Searching for such itemsets can be done both in datasets consisting of one large graph, and in datasets consisting of many graphs.
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