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This method is based on the principle of mining frequent patterns from such a dynamic graph and using the resulting patterns as indica- tors of sentence ...
Vol-2203/18⫷Vol-2203/28⫸Vol-2203/35. Matej Gallo Lubos Popelínský Karel Vaculík. To Text Summarization by Dynamic Graph Mining.
In this work, we propose Mango, an efficient method to summarize and un- derstand large dynamic graphs that extend beyond dense and isolated “cavemen” networks.
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Dynamic graph summarization is the task of obtaining and updating a summary of the current snapshot of a dynamic graph when changes (edge ...
Duration: 17:21
Posted: Jun 8, 2023
Posted: Jun 8, 2023
Sep 9, 2020 · We introduce the problem of subjective summarization of sequential data, and to solve this problem we propose the method of online summarization ...
Text summarization aims to compress a textual document to a short summary while keeping salient information. Extractive approaches are widely used in text ...
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Google's most famous algorithm, PageRank, is a method for computing importance scores for vertices of a directed graph. In addition to PageRank, we have ...
The related work falls into three main categories: static graph mining, temporal graph mining, and graph compression and sum- marization. Table 1 gives a ...
The approach involves constructing a text-graph, scanning the graph for summary candidate selection, and then adjusting it up to the set limit of length. The ...