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Title:Multi-Dimensional Analysis of Graph Data
Author(s):Chen, Chen
Doctoral Committee Chair(s):Han, Jiawei
Department / Program:Computer Science
Discipline:Computer Science
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Computer Science
Abstract: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.
Issue Date:2009
Type:Text
Language:English
Description:87 p.
Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.
URI:http://hdl.handle.net/2142/81857
Other Identifier(s):(MiAaPQ)AAI3391903
Date Available in IDEALS:2015-09-25
Date Deposited:2009


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