Mining Heterogeneous Information Networks: Principles and by Yizhou Sun,Jiawei Han

By Yizhou Sun,Jiawei Han

Real-world actual and summary information items are interconnected, forming enormous, interconnected networks. through structuring those information gadgets and interactions among those items into a number of kinds, such networks turn into semi-structured heterogeneous details networks. so much real-world functions that deal with gigantic facts, together with interconnected social media and social networks, clinical, engineering, or scientific details structures, on-line e-commerce platforms, and such a lot database structures, could be established into heterogeneous details networks. for this reason, potent research of large-scale heterogeneous details networks poses an engaging yet severe challenge.

In this e-book, we examine the rules and methodologies of mining heterogeneous info networks. Departing from many latest community types that view interconnected info as homogeneous graphs or networks, our semi-structured heterogeneous info community version leverages the wealthy semantics of typed nodes and hyperlinks in a community and uncovers unusually wealthy wisdom from the community. This semi-structured heterogeneous community modeling results in a chain of latest rules and strong methodologies for mining interconnected facts, together with: (1) rank-based clustering and type; (2) meta-path-based similarity seek and mining; (3) relation strength-aware mining, and plenty of different capability advancements. This booklet introduces this new study frontier and issues out a few promising study directions.

Table of Contents: creation / Ranking-Based Clustering / class of Heterogeneous details Networks / Meta-Path-Based Similarity seek / Meta-Path-Based dating Prediction / Relation Strength-Aware Clustering with Incomplete Attributes / User-Guided Clustering through Meta-Path choice / examine Frontiers

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