TY - GEN
T1 - Automatic construction of knowledge graphs from text and structured data
T2 - 3rd Conference on Language, Data and Knowledge, LDK 2021
AU - Masoud, Maraim
AU - Pereira, Bianca
AU - McCrae, John
AU - Buitelaar, Paul
N1 - Publisher Copyright:
© Maraim Masoud, Bianca Pereira, John McCrae, and Paul Buitelaar; licensed under Creative Commons License CC-BY 4.0
PY - 2021/8/1
Y1 - 2021/8/1
N2 - Knowledge graphs have been shown to be an important data structure for many applications, including chatbot development, data integration, and semantic search. In the enterprise domain, such graphs need to be constructed based on both structured (e.g. databases) and unstructured (e.g. textual) internal data sources; preferentially using automatic approaches due to the costs associated with manual construction of knowledge graphs. However, despite the growing body of research that leverages both structured and textual data sources in the context of automatic knowledge graph construction, the research community has centered on either one type of source or the other. In this paper, we conduct a preliminary literature review to investigate approaches that can be used for the integration of textual and structured data sources in the process of automatic knowledge graph construction. We highlight the solutions currently available for use within enterprises and point areas that would benefit from further research.
AB - Knowledge graphs have been shown to be an important data structure for many applications, including chatbot development, data integration, and semantic search. In the enterprise domain, such graphs need to be constructed based on both structured (e.g. databases) and unstructured (e.g. textual) internal data sources; preferentially using automatic approaches due to the costs associated with manual construction of knowledge graphs. However, despite the growing body of research that leverages both structured and textual data sources in the context of automatic knowledge graph construction, the research community has centered on either one type of source or the other. In this paper, we conduct a preliminary literature review to investigate approaches that can be used for the integration of textual and structured data sources in the process of automatic knowledge graph construction. We highlight the solutions currently available for use within enterprises and point areas that would benefit from further research.
KW - Enterprise knowledge graph
KW - Knowledge graph construction
UR - https://www.scopus.com/pages/publications/85115079222
U2 - 10.4230/OASIcs.LDK.2021.19
DO - 10.4230/OASIcs.LDK.2021.19
M3 - Conference Publication
AN - SCOPUS:85115079222
T3 - OpenAccess Series in Informatics
BT - 3rd Conference on Language, Data and Knowledge, LDK 2021
A2 - Gromann, Dagmar
A2 - Serasset, Gilles
A2 - Declerck, Thierry
A2 - McCrae, John P.
A2 - Gracia, Jorge
A2 - Bosque-Gil, Julia
A2 - Bobillo, Fernando
A2 - Heinisch, Barbara
PB - Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing
Y2 - 1 September 2021 through 3 September 2021
ER -