6 research outputs found

    Graph Hybrid Summarization

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    One solution to process and analysis of massive graphs is summarization. Generating a high quality summary is the main challenge of graph summarization. In the aims of generating a summary with a better quality for a given attributed graph, both structural and attribute similarities must be considered. There are two measures named density and entropy to evaluate the quality of structural and attribute-based summaries respectively. For an attributed graph, a high quality summary is one that covers both graph structure and its attributes with the user-specified degrees of importance. Recently two methods has been proposed for summarizing a graph based on both graph structure and attribute similarities. In this paper, a new method for hybrid summarization of a given attributed graph has proposed and the quality of the summary generated by this method has compared with the recently proposed method for this purpose. Experimental results showed that our proposed method generates a summary with a better quality

    Automatically Generating Citation Graphs (and Variants) for Systematic Reviews

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    Citation graphs visualize citation relationships of publications. Hence citation graphs enable in-depth analysis about the impact of publications to research areas, such that citation graphs have great benefits for systematic reviews about a special field of research. In this contribution, we introduce a tool for automatically generating citation graphs from a set of paper documents, which runs stand-alone or integrated in a systematic reviews application. As systematic reviews often include many papers, we also propose several strategies to reduce the complexity of citation graphs and add additional information for in-depth analysis of the impact of single publications. In addition to citation graphs our tool also visualizes the publication selection process of systematic reviews. The generated graphs and developed strategies are evaluated using different instruments, including an user survey, in which they are rated positively

    Distributed Graph Summarization

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