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Article . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
ZENODO
Article . 2025
License: CC BY
Data sources: Datacite
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Computer Entity-oriented Search Models in the Tourism Sector

Authors: Naglaa Saeed Shehata; Asmaa Ibrahim ELhanfy;

Computer Entity-oriented Search Models in the Tourism Sector

Abstract

Entity-oriented search is an advanced type of search engine that moves beyond simple keyword matching to focus on retrieving information about specific tourism entities and their relationships. In the tourism sector, these entities are foundational and include hotels, attractions, cities, airports, airlines, and events. The core objective of this search approach is to extract precise, structured information about these tourism entities and their interconnections from diverse sources such as databases, travel-related web texts, and social media. These search models are designed to provide users with comprehensive, structured results. This allows potential tourists to find detailed answers to complex queries, such as: "Which five-star hotels near the Burj Khalifa allow pets?" Entity-oriented search engines rely on sophisticated techniques like Knowledge Graphs, semantic technologies, and machine learning algorithms to deeply understand the meaning of travel-related user queries. This ensures the delivery of highly accurate and personalized results, significantly enriching the experience of searching for trips and holidays.

Keywords

entity-oriented search, Knowledge Graphs, semantic technologies

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green