By Quan Zheng,David Skillicorn

Social Networks with wealthy facet Semantics introduces a brand new mechanism for representing social networks during which pairwise relationships might be drawn from quite a number life like probabilities, together with types of relationships, assorted strengths within the instructions of a couple, optimistic and damaging relationships, and relationships whose intensities switch with time. for every danger, the booklet exhibits easy methods to version the social community utilizing spectral embedding. It additionally exhibits tips on how to compose the suggestions in order that a number of part semantics will be modeled jointly, and the modeling recommendations are then utilized to a number datasets.


Features




  • Introduces the reader to problems with present social community research, and the necessity for richer representations of relationships between nodes, together with accounting for depth, path, sort, positive/negative, and altering intensities over time



  • Presents a unique mechanism to permit social networks with qualitatively other kinds of relationships to be defined and analyzed



  • Includes extensions to the $64000 means of spectral embedding, exhibits that they're mathematically good prompted and proves that their effects are appropriate



  • Shows the way to take advantage of embeddings to appreciate constructions inside of social networks, together with subgroups, positional value, hyperlink or side prediction, consistency of position in several contexts, and internet stream of homes via a node



  • Illustrates using the procedure for real-world difficulties for on-line social networks, legal and drug smuggling networks, and networks the place the nodes are themselves groups


Suitable for researchers and scholars in social community study, info technology, statistical studying, and similar parts, this booklet might help to supply a deeper knowing of real-world social networks.

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Social Networks with Rich Edge Semantics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series) by Quan Zheng,David Skillicorn


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