IVIS: Search and visualization on heterogeneous information networks

We build a system to support search and visualization on heterogeneous information networks. We first build our system on a specialized heterogeneous information network: DBLP. The system aims to facilitate people, especially computer science researchers, toward a better understanding and user experience about academic information networks. Then we extend our system to the Web. Our results are much more intuitive and knowledgeable than the simple top-k blue links from traditional search engines, and bring more meaningful structural results with correlated entities. We also investigate the ranking algorithm, and we show that the personalized PageRank and proposed Hetero-personalized PageRank outperform the TF-IDF ranking or mixture of TF-IDF and authority ranking. Our work opens several directions for future research.

Name thesis:degree_name

M.S.

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2011

Author dc:creator

• Yu, Yintao

Contributors dc:contributor

• Han, Jiawei

• Page Rank
• DBLP
• Heterogeneous information network
• Visualization
• Ranking
• Information Retrieval

Statement dc:rights

• Copyright 2010 Yintao Yu

Language dc:language

en

Handle dc:identifier

http://hdl.handle.net/2142/18550

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/18550