RankSQL: query algebra and optimization for relational top-k queries

By Chengkai Li, Kevin Chen-Chuan Chang, Ihab F. Ilyas, Sumin Song. ACM SIGMOD Conference, 2005

331 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/47ef171b092a4cbb8e9e11122887b5c3e7c6eee5

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Mohamed A. Soliman
2. George Beskales
3. Ihab F. Ilyas
4. Kevin Chen-Chuan Chang
5. Thomas Lukasiewicz
6. Philip S. Yu
7. Charu C. Aggarwal

In Information Systems

1. Mohamed A. Soliman
2. Ihab F. Ilyas
3. George Beskales
4. Kevin Chen-Chuan Chang
5. Thomas Lukasiewicz
6. Xu Chu
7. Jean-Baptiste Lamy

In Signal Processing

1. Mohamed A. Soliman
2. George Beskales
3. Ihab F. Ilyas
4. Thomas Lukasiewicz
5. Kevin Chen-Chuan Chang
6. Charu C. Aggarwal
7. Philip S. Yu
8. Jean-Baptiste Lamy

Citations in the corpus

• Top-k Query Processing in Uncertain Databases (2007, methodology): “, [14, 17], to minimize the number of needed-to-access tuples.”
• A survey of top-k query processing techniques in relational database systems (2008, methodology): “These ideas are the foundations of the RankSQL system [Li et al. 2005], which introduces the first algebraic framework to support efficient evaluations of top-k queries in relational database systems.”
• Managing uncertainty and vagueness in description logics for the Semantic Web (2008, background): “, [31,60,75]), very few is known for the case of first-order knowledge bases in general (but see [136]) and description logics in particular.”