Advanced search
2 files | 1.51 MB Add to list

A file-based linked data fragments approach to prefix search

Ruben Dedecker (UGent) , Harm Delva (UGent) , Pieter Colpaert (UGent) and Ruben Verborgh (UGent)
Author
Organization
Abstract
Text-fields that need to look up specific entities in a dataset can be equipped with autocompletion functionality. When a dataset becomes too large to be embedded in the page, setting up a full-text search API is not the only alternative. Alternate API designs that balance different trade-offs such as archivability, cacheability and privacy, may not require setting up a new back-end architecture. In this paper, we propose to perform prefix search over a fragmentation of the dataset, enabling the client to take part in the query execution by navigating through the fragmented dataset. Our proposal consists of (i) a self-describing fragmentation strategy, (ii) a client search algorithm, and (iii) an evaluation of the proposed solution, based on a small dataset of 73k entities and a large dataset of 3.87 m entities. We found that the server cache hit ratio is three times higher compared to a server-side prefix search API, at the cost of a higher bandwidth consumption. Nevertheless, an acceptable user-perceived performance has been measured: assuming 150 ms as an acceptable waiting time between keystrokes, this approach allows 15 entities per prefix to be retrieved in this interval. We conclude that an alternate set of trade-offs has been established for specific prefix search use cases: having added more choice to the spectrum of Web APIs for autocompletion, a file-based approach enables more datasets to afford prefix search.

Downloads

  • DS425 acc.pdf
    • full text (Accepted manuscript)
    • |
    • open access
    • |
    • PDF
    • |
    • 778.87 KB
  • (...).pdf
    • full text (Published version)
    • |
    • UGent only
    • |
    • PDF
    • |
    • 735.37 KB

Citation

Please use this url to cite or link to this publication:

MLA
Dedecker, Ruben, et al. “A File-Based Linked Data Fragments Approach to Prefix Search.” Web Engineering, 21st International Conference, ICWE 2021, Proceedings, edited by Marco Brambilla et al., vol. 12706, Springer, 2021, pp. 53–67, doi:10.1007/978-3-030-74296-6_5.
APA
Dedecker, R., Delva, H., Colpaert, P., & Verborgh, R. (2021). A file-based linked data fragments approach to prefix search. In M. Brambilla, R. Chbeir, F. Frasincar, & I. Manolescu (Eds.), Web Engineering, 21st International Conference, ICWE 2021, Proceedings (Vol. 12706, pp. 53–67). Biarritz, France: Springer. https://doi.org/10.1007/978-3-030-74296-6_5
Chicago author-date
Dedecker, Ruben, Harm Delva, Pieter Colpaert, and Ruben Verborgh. 2021. “A File-Based Linked Data Fragments Approach to Prefix Search.” In Web Engineering, 21st International Conference, ICWE 2021, Proceedings, edited by Marco Brambilla, Richard Chbeir, Flavius Frasincar, and Ioana Manolescu, 12706:53–67. Springer. https://doi.org/10.1007/978-3-030-74296-6_5.
Chicago author-date (all authors)
Dedecker, Ruben, Harm Delva, Pieter Colpaert, and Ruben Verborgh. 2021. “A File-Based Linked Data Fragments Approach to Prefix Search.” In Web Engineering, 21st International Conference, ICWE 2021, Proceedings, ed by. Marco Brambilla, Richard Chbeir, Flavius Frasincar, and Ioana Manolescu, 12706:53–67. Springer. doi:10.1007/978-3-030-74296-6_5.
Vancouver
1.
Dedecker R, Delva H, Colpaert P, Verborgh R. A file-based linked data fragments approach to prefix search. In: Brambilla M, Chbeir R, Frasincar F, Manolescu I, editors. Web Engineering, 21st International Conference, ICWE 2021, Proceedings. Springer; 2021. p. 53–67.
IEEE
[1]
R. Dedecker, H. Delva, P. Colpaert, and R. Verborgh, “A file-based linked data fragments approach to prefix search,” in Web Engineering, 21st International Conference, ICWE 2021, Proceedings, Biarritz, France, 2021, vol. 12706, pp. 53–67.
@inproceedings{8709018,
  abstract     = {{Text-fields that need to look up specific entities in a dataset can be equipped with autocompletion functionality. When a dataset becomes too large to be embedded in the page, setting up a full-text search API is not the only alternative. Alternate API designs that balance different trade-offs such as archivability, cacheability and privacy, may not require setting up a new back-end architecture. In this paper, we propose to perform prefix search over a fragmentation of the dataset, enabling the client to take part in the query execution by navigating through the fragmented dataset. Our proposal consists of (i) a self-describing fragmentation strategy, (ii) a client search algorithm, and (iii) an evaluation of the proposed solution, based on a small dataset of 73k entities and a large dataset of 3.87 m entities. We found that the server cache hit ratio is three times higher compared to a server-side prefix search API, at the cost of a higher bandwidth consumption. Nevertheless, an acceptable user-perceived performance has been measured: assuming 150 ms as an acceptable waiting time between keystrokes, this approach allows 15 entities per prefix to be retrieved in this interval. We conclude that an alternate set of trade-offs has been established for specific prefix search use cases: having added more choice to the spectrum of Web APIs for autocompletion, a file-based approach enables more datasets to afford prefix search.}},
  author       = {{Dedecker, Ruben and Delva, Harm and Colpaert, Pieter and Verborgh, Ruben}},
  booktitle    = {{Web Engineering, 21st International Conference, ICWE 2021, Proceedings}},
  editor       = {{Brambilla, Marco and Chbeir, Richard and Frasincar, Flavius and Manolescu, Ioana}},
  isbn         = {{9783030742959}},
  issn         = {{0302-9743}},
  language     = {{eng}},
  location     = {{Biarritz, France}},
  pages        = {{53--67}},
  publisher    = {{Springer}},
  title        = {{A file-based linked data fragments approach to prefix search}},
  url          = {{http://dx.doi.org/10.1007/978-3-030-74296-6_5}},
  volume       = {{12706}},
  year         = {{2021}},
}

Altmetric
View in Altmetric