Summarizing static and dynamic big graphs

• المؤلفون الرئيسيون: Khan, Arijit, Bhowmick, Sourav Saha, Bonchi, Francesco
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2019
• الموضوعات: Engineering::Computer science and engineering; Query Processing; Visualization
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/105715; http://hdl.handle.net/10220/49546
• المؤسسة: Nanyang Technological University

Large-scale, highly-interconnected networks pervade our society and the natural world around us, including the World Wide Web, social networks, knowledge graphs, genome and scientific databases, medical and government records. The massive scale of graph data often surpasses the available computation and storage resources. Besides, users get overwhelmed by the daunting task of understanding and using such graphs due to their sheer volume and complexity. Hence, there is a critical need to summarize large graphs into concise forms that can be more easily visualized, processed, and managed. Graph summarization has indeed attracted a lot of interests from various research communities, such as sociology, physics, chemistry, bioinformatics, and computer science. Different ways of summarizing graphs have been invented that are often complementary to each other. In this tutorial, we discuss algorithmic advances on graph summarization in the context of both classical (e.g., static graphs) and emerging (e.g., dynamic and stream graphs) applications. We emphasize the current challenges and highlight some future research directions.