Ranking-based processing of SQL queries

A growing number of applications are built on top of search engines and issue complex structured queries. This paper contributes a customisable ranking-based processing of such queries, specifically SQL. Similar to how term-based statistics are exploited by term-based retrieval models, rankingaware processing of SQL queries exploits tuple-based statistics that are derived from sources or, more precisely, derived from the relations specified in the SQL query. To implement this ranking-based processing, we leverage PSQL, a probabilistic variant of SQL, to facilitate probability estimation and the generalisation of document retrieval models to be used for tuple retrieval. The result is a general-purpose framework that can interpret any SQL query and then assign a probabilistic retrieval model to rank the results of that query. The evaluation on the IMDB and Monster benchmarks proves that the PSQL-based approach is applicable to (semi-)structured and unstructured data and structured que...

• Type: Journal
• Year: 2011
• Where: CIKM
• Authors: Hany Azzam, Thomas Roelleke, Sirvan Yahyaei
• Keywords: CIKM 2011, Information Storage And Retrieval, Information Technology, Probability Estimation, Retrieval Models