A Knowledge Base Approach to Cross-Lingual Keyword Query Interpretation

The amount of entities in large knowledge bases available on the Web has been increasing rapidly, making it possible to propose new ways of intelligent information access. In addition, there is an impending need for technologies that can enable cross-lingual information access. As a simple and intuitive way of specifying information needs, keyword queries enjoy widespread usage, but suffer from the challenges including ambiguity, incompleteness and cross-linguality. In this paper, we present a knowledge base approach to cross-lingual keyword query interpretation by transforming keyword queries in different languages to their semantic representation, which can facilitate query disambiguation and expansion, and also bridge language barriers. The experimental results show that our approach achieves both high efficiency and effectiveness and considerably outperforms the baselines.