Abstract
ABSTRACT The rapid growth of cultural tourism, driven by the ‘heritage boom’, has brought about the urgent need to reduce the cost and broaden the audience of cultural tourism. To address this challenge, this paper proposes OACTD, an ontology-embedded model for heritage tourism reviews to assign cultural tourism data. The OACTD model integrates scattered and unstructured tourist reviews, making them directly beneficial to cultural tourists and related management organizations, while also reducing the costs of tourism. The model first integrates large volumes of tourist reviews from various popular tourism platforms, and then utilizes natural language processing (NLP) algorithms to extract key information. This information is subsequently structured and visualized through an ontology model, which is further enhanced based on tourist queries. To demonstrate the effectiveness of the model, a case study was conducted on the Xiangjiang Ancient Town Group, involving the extraction of key information and the construction of an ontology from 8016 tourist reviews. This study presents a novel approach to leveraging cultural tourism data, promoting the formation of a two-way ‘demand-supply’ digital cultural tourism ecological chain.
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