Abstract
We propose an approach to dynamically generate database schemas for well-formed XML data. Our approach controls the number of tables to be divided based on statistics of XML so that the total cost of processing queries is reduced. We devise schemas appropriate for complex data such as text formatting and child elements with the small maximum number of occurrences in order to reduce the number of tables. To this end, we define three functions NULL expectation, Large Leaf Fields, and Large Child Fields for controlling the tables to be divided. We evaluated typical XML queries over the generated schemas and normalized schemas and measured and compared both of the costs. Through this, we successfully validated our approach.
| Original language | English |
|---|---|
| Title of host publication | Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings |
| Pages | 379-390 |
| Number of pages | 12 |
| Publication status | Published - Dec 1 2005 |
| Externally published | Yes |
| Event | 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 - Melbourne, Australia Duration: Sep 14 2005 → Sep 16 2005 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 3681 LNAI |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 9th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2005 |
|---|---|
| Country | Australia |
| City | Melbourne |
| Period | 9/14/05 → 9/16/05 |
Fingerprint
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Ishikawa, H., Yokoyama, S., Ohta, M., & Katayama, K. (2005). On mining XML structures based on statistics. In Knowledge-Based Intelligent Information and Engineering Systems - 9th International Conference, KES 2005, Proceedings (pp. 379-390). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3681 LNAI).