A Graph Drawing Application to Web Site Traffic Analysis

Didimo, Walter; Liotta, Giuseppe; Romeo, Salvatore

doi:10.7155/jgaa.00224

Cited by 7 publications

(5 citation statements)

References 26 publications

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“…RAC (Right Angle Crossing) graphs are those graphs that admit a drawing where edges cross only at right angles (see, e.g., [21]). Several algorithms and systems for computing RAC drawings or, more in general, large angle crossing drawings, have been described in the literature (see, e.g., [5,17,18,19,24,25,42,35]). See also [23] for a survey.…”

Section: Introductionmentioning

confidence: 99%

Recognizing and drawing IC-planar graphs

Brandenburg

Didimo

Evans

et al. 2016

Theoretical Computer Science

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Section: Introductionmentioning

confidence: 99%

Recognizing and drawing IC-planar graphs

Brandenburg

Didimo

Evans

et al. 2016

Theoretical Computer Science

Self Cite

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“…Because of their wide applicability and because they also offer a straightforward graphical representation of the data, bipartite graphs have been recently used in the design of a website traffic analysis system [6]. Finally, Kaski et al [12] studied homophily in gene networks (similarity in gene expressions) in bio-informatics with emphasis on the trustworthiness of similarities, which places it close in spirit to our work.…”

Section: Introductionmentioning

confidence: 78%

Assessing group cohesion in homophily networks

Renoust

Mélançon

Viaud

2013

Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining

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The analysis and exploration of a social network depends on the type of relations at play. Borgatti had proposed a type taxonomy organizing relations in four possible categories. Homophily (similarity) relationships form an important category where relations occur when entities of the network link whenever they exhibit similar behaviors. Examples are networks of coauthor, where homophily between two persons follows from co-authorship; or network of actors having played under the supervision of the same movie director, for instance. Homophily is often embodied through a bipartite network where entities of a given type A (authors, movie directors) connect through entities of a different type B (papers, actors). A common strategy is then to project this bipartite graph onto a single-type network with entities of a same type A , possibly weighting edges based on how the type A entities interact with the type B entities underlying the edge. The resulting single-type network can then be studied using standard techniques such as community detection using edge density, or the computation of various centrality indices. This paper revisits this type of approach and introduces a homogeneity measure inspired form past work by Burt. Two entities of type B interact when they both induce a same edge between two entities of type A . The homogeneity of a subgroup thus depends on how intensely and how equally interactions occur between entities of type B giving rise to the subgroup. The measure thus differentiates between subgroups of type A exhibiting similar topologies depending on the interaction patterns of the underlying entities of type B. The method is validated using two widely used datasets. A first example looks at authors of the IEEE InfoVis Conference (InfoVis 2007 Contest). A second example looks at homophily relations between movie actors that have played under the direction of a same director (IMDB).

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“…9(c)); each curve is monotone in the direction of the straight-line segment connecting its end-points. The algorithm is also applied to the simultaneous embedding of suitably defined networks in a system for conceptual Web-site traffic analysis [109].…”

Section: Experiments and Engineeringmentioning

confidence: 99%