Open Access
Peer-Reviewed
Original Research
Folksonomies Versus Automatic Keyword Extraction: an Empirical Study
Abstract
Semantic Metadata, which describes the meaning of documents, can be produced either manually or else semi-automatically using information extraction techniques. Manual techniques are expensive if they rely on skilled cataloguers, but a po ssible alternative is to make use of community produced annotations such as those collected in folks onomies. This paper reports on an experiment that we carried out to validate the assumption that folksonomies contain hi gher semantic value than
Keywords
extracted by machines
Declarations & Ethics
Funding:
This research received academic dissemination support through ESCAP / JournalsHub publishing programs.
Conflicts of Interest:
The authors declare no competing financial or institutional interests.
Peer Review:
Double-blind peer reviewed by international subject specialists.
License:
Creative Commons Attribution 4.0 International (CC BY 4.0).
How to Cite This Article
APA / MLA / BibTeX
Al-Khalifa, et al. (2006). Folksonomies Versus Automatic Keyword Extraction: an Empirical Study. IADIS International Journal on Computer Science and Information Systems, 1(2). https://doi.org/10.33965/ijcsis_2006_v1i2_11
Al-Khalifa, et al. "Folksonomies Versus Automatic Keyword Extraction: an Empirical Study." IADIS International Journal on Computer Science and Information Systems, vol. 1, no. 2, 2006. https://doi.org/10.33965/ijcsis_2006_v1i2_11
Al-Khalifa, et al. "Folksonomies Versus Automatic Keyword Extraction: an Empirical Study." IADIS International Journal on Computer Science and Information Systems 1, no. 2 (2006). https://doi.org/10.33965/ijcsis_2006_v1i2_11