Cited by 58Semantic Web and OntologiesRecommender Systems and TechniquesInnovation in Digital Healthcare Systems

Connecting Destinations with an Ontology-Based e-Tourism Planner

Jakkilinki, Roopa, Georgievski, Mladen, Sharda, Nalin·2007·Information and Communication Technologies in Tourism 2007

Integrity signals

Registry

Crossref · 10.1007/978-3-211-69566-1_3

Cites

Statistics

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Claims other papers make about this one

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  • Jakkilinki, Georgievski, and Sharda (2007) proposed an ontology-based eTourism Planner -AuSTO that enables users to create itinerary in one single application by this intelligent tool that builds on semantic web technologies.

    “Jakkilinki, Georgievski, and Sharda (2007) proposed an ontology-based eTourism Planner -AuSTO that enables users to create itinerary in one single application by this intelligent tool that builds on semantic web technologies.”

Authors
Jakkilinki, R., Georgievski, M., & Sharda, N.
Affiliations
Victoria University (AU)
Venue
Information and Communication Technologies in Tourism 2007
Published
2007-04-15
Pages
21-32
OpenAlex
W1559948541
Cited by
58
References
0
Citations by year
2026: 1 · 2025: 4 · 2021: 2 · 2020: 3 · 2019: 1 · 2018: 4 · 2017: 1 · 2016: 5 · 2015: 5 · 2014: 6 · 2013: 3 · 2012: 5
FWCI
4.54
Type
book chapter
Language
en
Open access
closed
Locations
  • Springer eBooks (publishedVersion)
  • Victoria University Research Repository (Victoria University) (submittedVersion)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Health Sciences › Health Professions › Health Information Management › Innovation in Digital Healthcare Systems
Keywords
digital tourism, semantic web, ontology (information science), expert systems

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

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