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.
|Published in||Proceedings of the 26th IEEE International Conference on Data Engineering (ICDE 2010)|
|Publisher||IEEE Computer Society|