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Title:Mining heterogeneous information networks
Author(s):Sun, Yizhou
Director of Research:Han, Jiawei
Doctoral Committee Chair(s):Han, Jiawei
Doctoral Committee Member(s):Zhai, ChengXiang; Roth, Dan; Aggarwal, Charu C.
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):information network
social network
heterogeneous information network
data mining
network schema
similarity search
relationship prediction
user-guided meta-path selection
relation strength-aware mining
Abstract:Real-world physical objects and abstract data entities are interconnected, forming gigantic networks. By structuring these objects and their interactions into multiple types, such networks become semi-structured heterogeneous information networks. Most real-world applications that handle big data, including interconnected social media and social networks, scientific, engineering, or medical information systems, online e-commerce systems, and most database systems, can be structured into heterogeneous information networks. Therefore, effective analysis of large-scale heterogeneous information networks poses an interesting but critical challenge. In my thesis, I investigate the principles and methodologies of mining heterogeneous information networks. Departing from many existing network models that view interconnected data as homogeneous graphs or networks, our semi-structured heterogeneous information network model leverages the rich semantics of typed nodes and links in a network and uncovers surprisingly rich knowledge from the network. This semi-structured heterogeneous network modeling leads to a series of new principles and powerful methodologies for mining interconnected data, including (1) ranking-based clustering, (2) meta-path-based similarity search and mining, (3) user-guided relation strength-aware mining, and many other potential developments. This thesis introduces this new research frontier and points out some promising research directions.
Issue Date:2013-02-03
Rights Information:Copyright 2012 Yizhou Sun
Date Available in IDEALS:2013-02-03
Date Deposited:2012-12

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