Ripple Down Rules for question answering

Dat Quoc Nguyen*, Dai Quoc Nguyen, Son Bao Pham

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)


Recent years have witnessed a new trend of building ontology-based question answering systems. These systems use semantic web information to produce more precise answers to users' queries. However, these systems are mostly designed for English. In this paper, we introduce an ontology-based question answering system named KbQAS which, to the best of our knowledge, is the first one made for Vietnamese. KbQAS employs our question analysis approach that systematically constructs a knowledge base of grammar rules to convert each input question into an intermediate representation element. KbQAS then takes the intermediate representation element with respect to a target ontology and applies concept-matching techniques to return an answer. On a wide range of Vietnamese questions, experimental results show that the performance of KbQAS is promising with accuracies of 84.1% and 82.4% for analyzing input questions and retrieving output answers, respectively. Furthermore, our question analysis approach can easily be applied to new domains and new languages, thus saving time and human effort.

Original languageEnglish
Pages (from-to)511-532
Number of pages22
JournalSemantic Web
Issue number4
Publication statusPublished - 2017


  • Question answering
  • question analysis
  • Single Classification Ripple Down Rules
  • knowledge acquisition
  • ontology
  • Vietnamese
  • English
  • DBpedia
  • biomedical


Dive into the research topics of 'Ripple Down Rules for question answering'. Together they form a unique fingerprint.

Cite this