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Pivoted table index for querying product-property-value information
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Source Conference On Ubiquitous Information Management And Communication archive
Proceedings of the 3rd International Conference on Ubiquitous Information Management and Communication table of contents
Suwon, Korea
SESSION: Data search I table of contents
Pages 58-62  
Year of Publication: 2009
ISBN:978-1-60558-405-8
Authors
Hyunja Lee  Sookmyung Women's University, Yongsan-gu, Seoul, Korea
Junho Shim  Sookmyung Women's University, Yongsan-gu, Seoul, Korea
Sponsor
SIGKDD: ACM Special Interest Group on Knowledge Discovery in Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

The query for triple information on product -attribute (property)-value is one of the most frequent queries in e-commerce. Storing the triple, schema vertically is effective for avoidance of sparse data and schema evolution. However, conventional horizontal schema often shows better query performance when properties are queried as groups clustered by product. Therefore, we propose vertical schema as a primary table structure for the triple information in RDBMS and a pivoted table index created from the basic vertical table. This index is beneficial to performance of the frequent pattern query on the group properties associated with each product class.


REFERENCES

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5
 
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J. Corwin, A. Silberschatz, P. L. Miller, and L. Marenco. Dynamic tables: An architecture for managing evolving, heterogeneous biomedical data in relational database management systems. Journal of the American Medical Informatics Association, 14(1):86--93, 2007
7
 
8
D. Valentin, P. Nadkarni, and C. Brandt, Pivoting approaches for bulk extraction of Entity-Attribute-Value data Comp Meth Programs Biomed 2006;82: 38--43, 2006.
 
9
 
10
Z. H. Liu, M. Krishnaprasad, H. J. Chang, and V. Arora, XML Table Index -- An Efficient Way of Indexing and Querying XML Property Data, In Proc. of ICDE2007,2007
 
11
T. Lee, I. Lee, S. Lee, S. Lee, D. Kim, J. Chun, H. Lee, and J. Shim, Building an Operational Product Ontology System, Electronic Commerce Research and Applications, 2006.
 
12
 
13
 
14
Z. Pan and J. Heflin, DLDB: Extending Relational Databases to Support Semantic Web Queries, In Proc. of International Workshop on Practical and Scalable Semantic Web Systems, 2003.
 
15
R. Volz, D. Oberle, S. Staab, and B. Motik, KAON SERVER - A Semantic Web Management System, In Proc. of WWW2003, 2003
 
16
K. Wilkinson. Jena property table implementation. In Proc. of SSWS, 2006.
 
17
K. Wilkinson, C. Sayers, H. A. Kuno, and D. Reynolds, Efficient RDF Storage and Retrieval in Jena2, In Proc. of SWDB, 2003