XKnowSearch! Exploiting Knowledge Bases for Entity-based Cross-lingual Information Retrieval

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.

Demo:


Online System:

  • XKnowSearch! (Chrome and Safari are recommended. Currently Firefox has a problem with the Demo. Please note that the performance of the server is low.)

Publications:

  • 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




(c) 2015-2016 Lei Zhang, Institute AIFB, KIT