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» G-hash: towards fast kernel-based similarity search in large...
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EDBT
2009
ACM
277views Database» more  EDBT 2009»
13 years 9 months ago
G-hash: towards fast kernel-based similarity search in large graph databases
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald ...
BIBM
2009
IEEE
206views Bioinformatics» more  BIBM 2009»
13 years 11 months ago
Application of Kernel Functions for Accurate Similarity Search in Large Chemical Databases
Background: Similaritysearch in chemical structure databases is an important problem with many applications in chemical genomics, drug design, and efficient chemical probe screeni...
Xiaohong Wang, Jun Huan, Aaron M. Smalter, Gerald ...
SIGMOD
2011
ACM
241views Database» more  SIGMOD 2011»
12 years 7 months ago
Neighborhood based fast graph search in large networks
Complex social and information network search becomes important with a variety of applications. In the core of these applications, lies a common and critical problem: Given a labe...
Arijit Khan, Nan Li, Xifeng Yan, Ziyu Guan, Supriy...
SIGMOD
2005
ACM
178views Database» more  SIGMOD 2005»
14 years 4 months ago
Towards Effective Indexing for Very Large Video Sequence Database
With rapid advances in video processing technologies and ever fast increments in network bandwidth, the popularity of video content publishing and sharing has made similarity sear...
Heng Tao Shen, Beng Chin Ooi, Xiaofang Zhou
JCP
2008
171views more  JCP 2008»
13 years 4 months ago
Mining Frequent Subgraph by Incidence Matrix Normalization
Existing frequent subgraph mining algorithms can operate efficiently on graphs that are sparse, have vertices with low and bounded degrees, and contain welllabeled vertices and edg...
Jia Wu, Ling Chen