Bolin Ding, Bo Zhao, Cindy Xide Lin, Jiawei Han, and Chengxiang Zhai
Previous studies on supporting keyword queries in RDBMSs provide users with a ranked list of relevant linked structures (e.g. joined tuples) or individual tuples. In this paper, we aim to support keyword search in a data cube with text-rich dimension(s) (so-called text cube). Each document is associated with structural dimensions. A cell in the text cube aggregates a set of documents with matching dimension values on a subset of dimensions. Given a keyword query, our goal is to find the top-k most relevant cells in the text cube. We propose a relevance scoring model and efficient ranking algorithms. Experiments are conducted to verify their efficiency.
In Proceedings of the 26th IEEE International Conference on Data Engineering (ICDE 2010)
Publisher IEEE Computer Society