Multi-Dimensional Analysis of Graph Data

In conclusion, the multi-dimensional analysis framework could lead to intuitive and insightful knowledge discovery on graphs, especially when the data is large and complex. Given the emerging trend of huge information networks as listed above, it is an important research topic to devote more efforts to. We point out a few possible future works, especially discovery-driven Graph OLAP. We believe that this is an interesting direction to go, and give our initial thoughts on it.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Computer Science

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Chen, Chen

Contributors dc:contributor

• Han, Jiawei

• Computer Science

Language dc:language

eng

Identifier

(MiAaPQ)AAI3391903

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/81857