From XML schema to relations: a cost-based approach to XML storage
By Philip Bohannon, Juliana Freire, Prasan Roy, Jérôme Siméon. Proceedings / International Conference on Data Engineering, 2002
351 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing
View Paper: https://www.semanticscholar.org/paper/412ac9df9f110772a9b952da4be404da7d4c3c3b
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Computer Networks and Communications
- Yannis Papakonstantinou
- Vagelis Hristidis
- Andrey Balmin
- Stratis Viglas
- Jayavel Shanmugasundaram
- Eugene J. Shekita
- Luis Gravano
- Hanghang Tong
In Signal Processing
- Yannis Papakonstantinou
- Vagelis Hristidis
- Andrey Balmin
- Stratis Viglas
- Jayavel Shanmugasundaram
- Luis Gravano
- Hanghang Tong
- Philip S. Yu
Citations in the corpus
- Storing and querying ordered XML using a relational database system (2002, methodology): “Researchers have proposed using relational database systems to satisfy these requirements by devising ways to “shred” (i.e., decompose) XML documents into relations, and translate XML queries into SQL queries over these relations [1][4][7][11][13][14].”
- Keyword proximity search on XML graphs (2003, methodology): “XKeyword stores the XML data in a relational database [7, 19, 10, 16, 8, 18, 5], to allow the addition of structured querying capabilities in the future and leverage the indexing capabilities of the DBMS’s.”
- ORDPATHs: insert-friendly XML node labels (2004, neutral): “3), known as the NODE table; a shredding transformation [2], [8], [9] will”