Processing Relational Top-N Queries with Text and Numeric Attributes
Liang Zhu, Bin Liu, Guang Liu, Quan Long Lei · Applied Mechanics and Materials · 2014
Relational top-N queries with both text attributes and numeric attributes are useful in many applications, by using the ranking functions based on both semantic distances for text attributes and numeric distances for numeric attributes. In this paper, we propose an approach for processing such type of top-N queries in relational databases. The basic idea of the approach is to create an index based on WordNet to expand the tuple words semantically for text attributes and on the related information of numeric attributes, meanwhile the size of the index increases linearly with the size of the database. The results of extensive experiments show that our method is efficient and effective.