University of Illinois Urbana-Champaign

Entity recommendation and search in heterogeneous information networks

Yu, Xiao

Content Files
Xiao_Yu.pdf

Xiao_Yu.pdf

Download File Copy Link To File
Format
Portable Document Format
Media Type
application/pdf
Size
1.77 MB
API Resource
/items/49425/bitstreams/144037
Bundle
Content
Primary
NO
Downloads
1,208

Permalink

https://hdl.handle.net/2142/49374

Description

Title
Entity recommendation and search in heterogeneous information networks
Author(s)
Yu, Xiao
Issue Date
2014-05-30T16:40:46Z
Director of Research (if dissertation) or Advisor (if thesis)
Han, Jiawei
Doctoral Committee Chair(s)
Han, Jiawei
Committee Member(s)
  • Zhai, ChengXiang
  • Huang, Thomas S.
  • Ma, Hao
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Date of Ingest
2014-05-30T16:40:46Z
Keyword(s)
  • entity recommendation
  • entity search
  • information network
Abstract
With the rapid development of social media and information network-based web services, data mining studies on network analysis have gained increasing attention in recent years. Many early studies focus on homogeneous network mining, with the assumption that the network nodes and links are of the same type (e.g., social networks). However, real-world data in many domains and applications are often multi-typed and interconnected, forming heterogeneous information networks. The objective of my thesis is to study effective and scalable approaches to help users explore and discover useful information and knowledge in heterogeneous information networks. I also aim to advance the principles and methodologies of mining heterogeneous information networks through these studies. Specifically, I study and focus on entity recommendation and search related problems in heterogeneous information networks. I investigate and propose data mining methodologies to facilitate the construction of entity recommender systems and search engines for heterogeneous networks. In this thesis, I first propose to study entity recommendation problem in heterogeneous information network scope with implicit feedback. Second, I study a real-world large-scale entity recommendation application with commercial search engine user logs and a web-scale entity graph. Third, I combine text information and heterogeneous relationships between entities to study citation prediction and search problem in bibliographical networks. Fourth, I introduce a user-guided entity similarity search framework in information networks to integrate users' guidance into entity search process, which helps alleviate entity similarity ambiguity problem in heterogeneous networks. The methodologies proposed in this thesis are critically important for information exploration in heterogeneous information networks. The principles and theoretical findings in these studies have potential impact in other information network related research fields and can be applied in a wide range of real-world applications.
Graduation Semester
2014-05
Permalink
http://hdl.handle.net/2142/49374
Copyright and License Information
Copyright 2014 Xiao Yu

Owning Collections

Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at Illinois
Dissertations and Theses - Computer Science
Dissertations and Theses from the Siebel School of Computer Science