Efficient Inverted Lists and Query Algorithms for Structured Value Ranking in Update-Intensive Relational Databases
21st International Conference on Data Engineering (ICDE'05) (2005)
Apr. 5, 2005 to Apr. 8, 2005
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDE.2005.59
Lin Guo , Cornell University
Jayavel Shanmugasundaram , Cornell University
Kevin Beyer , IBM Almaden Research Center
Eugene Shekita , IBM Almaden Research Center
We propose a new ranking paradigm for relational databases called Structured Value Ranking (SVR). SVR uses structured data values to score (rank) the results of keyword search queries over text columns. Our main contribution is a new family of inverted list indices and associated query algorithms that can support SVR efficiently in update-intensive databases, where the structured data values (and hence the scores of documents) change frequently. Our experimental results on real and synthetic data sets using BerkeleyDB show that we can support SVR efficiently in relational databases.
J. Shanmugasundaram, K. Beyer, L. Guo and E. Shekita, "Efficient Inverted Lists and Query Algorithms for Structured Value Ranking in Update-Intensive Relational Databases," 21st International Conference on Data Engineering (ICDE'05)(ICDE), Tokyo, Japan, 2005, pp. 298-309.