KBQA: Constructing structured query graph from keyword query for semantic search

Heewon Jang, Haemin Jung, Dongkyu Jeon, Yeongtaek Oh, Hyesoo Kong, Seunghee Jin, Dokyung Lee, Wooju Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


It is often very difficult to locate information on the Web because of its large and rapidly increasing amount of data. One key reason for this is traditional keyword-based search engines focus only on the resources whose title or content exactly matches the query keywords. People usually want to find the best matching resource itself to their query, not the documents which contain the resource. Recently, one promising way to meet this kind of requirement must be ontology-based approach for semantic search. However, it is also obvious there is still non-negligible gap between average users and ontological approach. To overcome this limitation of ontological approach such as Semantic Web, it is essential to provide an efficient method to fill the gap while taking full advantage of semantic technologies. To this end, we devise a method to generate alternative SPARQL queries from the typical natural language based query to the conventional search engines and evaluate the most matched SPARQL query among the alternatives by considering the characteristics of the target knowledge bases. We then implement a prototype system to evaluate the proposed method and validate its empirical performance and accuracy.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Electronic Commerce, ICEC 2017
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450353120
Publication statusPublished - 2017 Aug 17
Event2017 International Conference on Electronic Commerce, ICEC 2017 - Pangyo, Seongnam, Korea, Republic of
Duration: 2017 Aug 172017 Aug 18

Publication series

NameACM International Conference Proceeding Series


Conference2017 International Conference on Electronic Commerce, ICEC 2017
Country/TerritoryKorea, Republic of
CityPangyo, Seongnam

Bibliographical note

Funding Information:
This research was supported and funded by SK Telecom.

Publisher Copyright:
© Copyright 2017 ACM

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications


Dive into the research topics of 'KBQA: Constructing structured query graph from keyword query for semantic search'. Together they form a unique fingerprint.

Cite this