Building lightweight semantic search engines

Michael Rovatsos*, Rosa Filgueira*

*Corresponding author for this work

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

2 Downloads (Pure)


Despite significant advances in methods for processing large volumes of structured and unstructured data, surprisingly little attention has been devoted to developing general practical methodologies that leverage state-of-the-art technologies to build domain-specific semantic search engines tailored to use cases where they could provide substantial benefits. This paper presents a methodology for developing these kinds of systems in a lightweight, modular, and flexible way with a particular focus on providing powerful search tools in domains where non-expert users encounter challenges in exploring the data repository at hand. Using an academic expertise finder tool as a case study, we demonstrate how this methodology allows us to leverage powerful off-the-shelf technology to enable the rapid, low-cost development of semantic search engines, while also affording developers with the necessary flexibility to embed user-centric design in their development in order to maximise uptake and application value.
Original languageEnglish
Title of host publicationProceedings
Subtitle of host publication2023 IEEE 19th international conference on e-science (e-science)
EditorsGeorge Angelos Papadopoulos, Rosa Filgueira, Rafael Ferreira Da Silva
Place of PublicationPiscataway, NJ
Number of pages10
ISBN (Electronic)9798350322231
ISBN (Print)9798350322248
Publication statusPublished - 25 Sept 2023
Event19th IEEE International Conference on eScience - Limassol, Cyprus, Limassol, Cyprus
Duration: 9 Oct 202313 Oct 2023
Conference number: 19

Publication series

NameIEEE international conference on e-science
ISSN (Print)2325-372X
ISSN (Electronic)2325-3703


Conference19th IEEE International Conference on eScience
Abbreviated titleeScience
Internet address


  • Semantic search
  • Natural language technologies
  • Neural information retrieval
  • Knowledge graphs


Dive into the research topics of 'Building lightweight semantic search engines'. Together they form a unique fingerprint.

Cite this