Abstract: In recent years, 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. On the other hand, within the context of globalization, there is a clear need for technologies and systems that can enable multilingual and cross-lingual information access. In this paper, we demonstrate XKnowSearch!, a novel search system for multilingual and cross-lingual information retrieval, which supports traditional keyword search and also allows users to influence the search process according to their search intents. By exploiting multilingual knowledge bases on the Web, keyword queries and media data on the Web can be represented in their semantic forms, i.e., entities in knowledge bases, which facilitates query disambiguation and expansion, and also bridges the language barriers between queries and media data in different languages.
XKnowSearch! Exploiting Knowledge Bases for Entity-based Cross-lingual Information Retrieval
- The XKnowSearch! system is not accessible any more. Please check our new system BreXearch.
Institute AIFB, KIT
- XKnowSearch!: Exploiting Knowledge Bases for Entity-based Cross-lingual Information Retrieval [pdf]
Lei Zhang, Michael Färber, Achim Rettinger
CIKM 2016: 2425-2428
- A Knowledge Base Approach to Cross-Lingual Keyword Query Interpretation [pdf]
Lei Zhang, Achim Rettinger, Ji Zhang
International Semantic Web Conference (1) 2016: 615-631