Building XML data warehouse based on frequent patterns in user queries

[Abstract]: With the proliferation of XML-based data sources available across the Internet, it is increasingly important to provide users with a data warehouse of XML data sources to facilitate decision-making processes. Due to the extremely large amount of XML data available on web, unguided warehousing of XML data turns out to be highly costly and usually cannot well accommodate the users’ needs in XML data acquirement. In this paper, we propose an approach to materialize XML data warehouses based on frequent query patterns discovered from historical queries issued by users. The schemas of integrated XML documents in the warehouse are built using these frequent query patterns represented as Frequent Query Pattern Trees (FreqQPTs). Using hierarchical clustering technique, the integration approach in the data warehouse is flexible with respect to obtaining and maintaining XML documents. Experiments show that the overall processing of the same queries issued against the global schema become much efficient by using the XML data warehouse built than by directly searching the multiple data sources

Ant colony optimization based clustering for data partitioning.

Woo Kwan Ho.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.Includes bibliographical references (leaves 148-155).Abstracts in English and Chinese.Contents --- p.iiAbstract --- p.ivAcknowledgements --- p.viiList of Figures --- p.viiiList of Tables --- p.xChapter Chapter 1 --- Introduction --- p.1Chapter Chapter 2 --- Literature Reviews --- p.7Chapter 2.1 --- Block Clustering --- p.7Chapter 2.2 --- Clustering XML by structure --- p.10Chapter 2.2.1 --- Definition of XML schematic information --- p.10Chapter 2.2.2 --- Identification of XML schematic information --- p.12Chapter Chapter 3 --- Bi-Tour Ant Colony Optimization for diagonal clustering --- p.15Chapter 3.1 --- Motivation --- p.15Chapter 3.2 --- Framework of Bi-Tour Ant Colony Algorithm --- p.21Chapter 3.3 --- Re-order of the data matrix in BTACO clustering method --- p.27Chapter 3.3.1 --- Review of Ant Colony Optimization --- p.29Chapter 3.3.2 --- Bi-Tour Ant Colony Optimization --- p.36Chapter 3.4 --- Determination of partitioning scheme --- p.44Chapter 3.4.1 --- Weighed Sum of Error (WSE) --- p.48Chapter 3.4.2 --- Materialization of partitioning scheme via hypothetic matrix --- p.50Chapter 3.4.3 --- Search of best-fit hypothetic matrix --- p.52Chapter 3.4.4 --- Dynamic programming approach --- p.53Chapter 3.4.5 --- Heuristic partitioning approach --- p.57Chapter 3.5 --- Experimental Study --- p.62Chapter 3.5.1 --- Data set --- p.63Chapter 3.5.2 --- Study on DP Approach and HP Approach --- p.65Chapter 3.5.3 --- Study on parameter settings --- p.69Chapter 3.5.4 --- Comparison with GA-based & hierarchical clustering methods --- p.81Chapter 3.6 --- Chapter conclusion --- p.90Chapter Chapter 4 --- Application of BTACO-based clustering in XML database system --- p.93Chapter 4.1 --- Introduction --- p.93Chapter 4.2 --- Overview of normalization and vertical partitioning in relational DB design --- p.95Chapter 4.2.1 --- Normalization of relational models in database design --- p.95Chapter 4.2.2 --- Vertical partitioning in database design --- p.98Chapter 4.3 --- Clustering XML documents --- p.100Chapter 4.4 --- Proposed approach using BTACO-based clustering --- p.103Chapter 4.4.1 --- Clustering XML documents by structure --- p.103Chapter 4.4.2 --- Clustering XML documents by user transaction patterns --- p.109Chapter 4.4.3 --- Implementation of Query Manager for our experimental study --- p.114Chapter 4.5 --- Experimental Study --- p.118Chapter 4.5.1 --- Experimental Study on the clustering by structure --- p.118Chapter 4.5.2 --- Experimental Study on the clustering by user access patterns --- p.133Chapter 4.6 --- Chapter conclusion --- p.141Chapter Chapter 5 --- Conclusions --- p.143Chapter 5.1 --- Contributions --- p.144Chapter 5.2 --- Future works --- p.146Bibliography --- p.148Appendix I --- p.156Appendix II --- p.168Index tables for Profile A --- p.168Index tables for Profile B --- p.171Appendix III --- p.17

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