Correlation-based ranking for relational databases

Jaehui Park, Sang Goo Lee

Research output: Contribution to journalArticlepeer-review


There has been a great deal of interest in recent years on ranking query results in relational databases. This paper presents a novel method to rank objects (e.g., tuples) by exploiting the correlations among their attribute values. Given a query, each attribute value is assigned a score according to mutual occurrences with the query and its distribution status in the columns of the attribute. These attribute value scores are aggregated to get a final score for an object. Furthermore, a concept vector is proposed to provide a synopsis of the attribute value in a given database. A concept vector is utilized to get similar objects. Experimental results demonstrate the performance of our ranking method, RAVC (Ranking with Attribute Value Correlation), in terms of search quality and efficiency.

Original languageEnglish
Pages (from-to)4175-4191
Number of pages17
Issue number6 B
StatePublished - Jun 2013


  • Attribute Value Correlation
  • Attribute importance
  • Ranking function for structured data


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