![]() Esmaeilzadeh Dilmaghani, Saharnaz ![]() ![]() ![]() in 2019 IEEE International Conference on Big Data (Big Data), 9-12 December 2019 (2020, February 24) Detailed reference viewed: 150 (21 UL)![]() Esmaeilzadeh Dilmaghani, Saharnaz ![]() ![]() in Frontiers in Big Data (2019), 2 Detailed reference viewed: 91 (6 UL)![]() Esmaeilzadeh Dilmaghani, Saharnaz ![]() ![]() Scientific Conference (2019, February 25) We consider the problem of automatically generating networks from data of collaborating researchers. The objective is to apply network analysis on the resulting network layers to reveal supplemental ... [more ▼] We consider the problem of automatically generating networks from data of collaborating researchers. The objective is to apply network analysis on the resulting network layers to reveal supplemental patterns and insights of the research collaborations. In this paper, we describe our data-to-networks method, which automatically generates a set of logical network layers from the relational input data using a linkage threshold. We, then, use a series of network metrics to analyze the impact of the linkage threshold on the individual network layers. Moreover, results from the network analysis also provide beneficial information to improve the network visualization. We demonstrate the feasibility and impact of our approach using real-world collaboration data. We discuss how the produced network layers can reveal insights and patterns to direct the data analytics more intelligently. [less ▲] Detailed reference viewed: 130 (33 UL)![]() Samir Labib, Nader ![]() ![]() ![]() Report (2018) Detailed reference viewed: 166 (54 UL) |
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