A Two-phase Ranking Method for the Relational Databases
Yingqi Wang, Lianke Zhou, Hongbin Wang
International Journal of Computational Linguistics Research, Vol. 10, No. 1, 2019.
DOI: https://doi.org/10.6025/jcl/2019/10/1/1-12
Link: http://www.dline.info/jcl/fulltext/v10n1/jclv10n1_1.pdf
Abstract:
With the extensive application of keyword query in relational database, the ranking algorithm has become an important research topic. Most existing ranking methods have adopted IR-style ranking models without considering the effects
of semantic relevancy and diversity on the ranking results. In this paper, we propose a novel ranking method on the basis of
semantic relevancy and diversity. First, we define the concepts of basic semantics and complex semantics and then add them to
the ranking function. Next, aiming at the generation of redundancy, we design the diversity strategy to re-rank query results. Experimental results demonstrate that our method has better performance in terms of precision and recall.