Interactive Predicate Suggestion for Keyword Search on RDF Graphs

  • Mengxia Jiang
  • Yueguo Chen
  • Jinchuan Chen
  • Xiaoyong Du
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7121)


With the rapid growth of RDF data set, searching RDF data has recently received much attention. So far, structural languages such as SPARQL support to search RDF data efficiently and accurately. Unfortunately it requires users to have the prior knowledge of the underlying schema and query syntax of RDF data set. On the other hand, keyword search over graphs outperforms SPARQL queries in terms of usability. However, the predicate information is ignored in keyword queries, which results in the huge searching space and generates ambiguous interpretation of queries. In this paper, we design an interactive process of keyword search, which allows users to reduce the ambiguity of keywords by selecting some predicates to constrain the semantics of query keywords. We propose an efficient and effective algorithm to online discover a small number of predicates for users to choose. Experiments on the YAGO data set demonstrate the effectiveness and efficiency of our method.


Keyword Search Keyword Query SPARQL Query Matching Degree Predicate Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Mengxia Jiang
    • 1
    • 2
  • Yueguo Chen
    • 2
  • Jinchuan Chen
    • 2
  • Xiaoyong Du
    • 1
    • 2
  1. 1.School of InformationRenmin University of ChinaBeijingChina
  2. 2.Key Laboratory of Data Engineering and Knowledge Engineering, MOERenmin University of ChinaChina

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