DocumentCode :
1627895
Title :
Mining, Indexing, and Similarity Search in Graphs and Complex Structures
Author :
Han, Jiawei ; Yan, Xifeng ; Yu, Philip S.
Author_Institution :
Univ. of Illinois at Urbana-Champaign
fYear :
2006
Firstpage :
106
Lastpage :
106
Abstract :
Scalable methods for mining, indexing, and similarity search in graphs and other complex structures, such as trees, lattices, and networks, have become increasingly important in data mining and database management. This is because a large set of emerging applications need to handle new kinds of objects with complex structures, such as trees (e.g., XML data), graphs (e.g., Web, chemical structures and biological graphs) and networks (e.g., social and biological networks). Such complicated data structures pose many new challenging research problems related to data mining, data management, and similarity search that do not exist in the traditional database and data mining studies.
Keywords :
Application software; Clustering algorithms; Data mining; Indexing; Intelligent networks; Lattices; Protein sequence; Search methods; Spatial databases; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering, 2006. ICDE '06. Proceedings of the 22nd International Conference on
Print_ISBN :
0-7695-2570-9
Type :
conf
DOI :
10.1109/ICDE.2006.99
Filename :
1617474
Link To Document :
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