Ontologies for the classification of cultural heritage data

Nafis, Fouad; Yahyaouy, Ali; Aghoutane, Badraddine

doi:10.1109/wits.2019.8723850

Cited by 8 publications

(8 citation statements)

References 14 publications

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“…For that, a wide range of innovative technological solutions, such as NoSQL database management systems (Cassandra, MongoDB, : : :) and distributed file systems (Hadoop HDFS), are adopted. Other researches [30,31] also aim at enriching these data semantically by using Semantic Web technologies, especially ontologies, for more intelligent management and access.…”

Section: Methodology Of Integration Of Big Data and Ai For Implementi...mentioning

confidence: 99%

Hybrid recommender system for tourism based on big data and AI: A conceptual framework

Fararni

Nafis

Aghoutane

et al. 2021

Big Data Min. Anal.

104

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With the development of the Internet, technology, and means of communication, the production of tourist data has multiplied at all levels (hotels, restaurants, transport, heritage, tourist events, activities, etc.), especially with the development of Online Travel Agency (OTA). However, the list of possibilities offered to tourists by these Web search engines (or even specialized tourist sites) can be overwhelming and relevant results are usually drowned in informational "noise", which prevents, or at least slows down the selection process. To assist tourists in trip planning and help them to find the information they are looking for, many recommender systems have been developed. In this article, we present an overview of the various recommendation approaches used in the field of tourism. From this study, an architecture and a conceptual framework for tourism recommender system are proposed, based on a hybrid recommendation approach. The proposed system goes beyond the recommendation of a list of tourist attractions, tailored to tourist preferences. It can be seen as a trip planner that designs a detailed program, including heterogeneous tourism resources, for a specific visit duration. The ultimate goal is to develop a recommender system based on big data technologies, artificial intelligence, and operational research to promote tourism in Morocco, specifically in the Dara â-Tafilalet region.

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Section: Methodology Of Integration Of Big Data and Ai For Implementi...mentioning

confidence: 99%

Hybrid recommender system for tourism based on big data and AI: A conceptual framework

Fararni

Nafis

Aghoutane

et al. 2021

Big Data Min. Anal.

104

View full text Add to dashboard Cite

show abstract

“…The work carried out in this study is part of a project aimed at the publication and semantic integration of the region's heritage data. In [2] a study was conducted to compare the ontologies of heritage data classification and in [3] a system was proposed for the semantic integration of the data of the study region. Figure 3 provides Fig.…”

Section: Methodsmentioning

confidence: 99%

Towards an Integrated Platform for the Presentation and Preservation of the Scientific Heritage of Drâa-Tafilalet

Nafis

Aghoutane

Yahyaouy

2021

Lecture Notes in Electrical Engineering

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The region of Drâa-Tafilalet in the south-east of Morocco is known for its unique and varied tourist qualifications, combining the greenery of the oasis with the quietness of the desert and its deep-rooted heritage, which has made it one of the best known tourist poles at the national and international levels. The region has benefited from national programs aimed at promoting the tourism sector and restoring the rich and unique local heritage. This region has benefited from national programs aimed at promoting the tourism sector and restoring the rich and unique local heritage. The main objective of this article is to present the heritage of the Drâa Tafilalet region with emphasis on the diverse and rich scientific heritage in the region. This paper presents the latest results obtained in this field, based on applications, technologies, etc., aimed at preserving this heritage from extinction and presenting it to future generations.

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“…Following step (2) of the adopted design methodology, we investigated the realm of Cultural Heritage oriented ontologies (Kakali et al, 2007 ; Doerr, 2009 ; Nafis et al, 2019 ).…”

Section: Designing Paun Ontologymentioning

confidence: 99%

An Ontology-Based Chatbot to Enhance Experiential Learning in a Cultural Heritage Scenario

Casillo

Santo

Mosca

et al. 2022

Front. Artif. Intell.

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Italy is rich in cultural attractions, many known worldwide, others more hidden and unrecognized. Cultural attractions include tangible cultural assets (works of art, archaeological excavations, and churches) and intangible ones (music, poetry, and art). Today, given the pervasive diffusion of “smart” devices, the intelligent use of modern technologies could play a crucial role in changing the habit of consulting and visiting cultural heritage mainly with traditional methodologies, making little or no use of the advantages coming from the more and more availability of digitalized resources. A realm of particular interest is “experiential learning” when applied to cultural heritage, where tourists more and more ask to be helped in discovering the richness of sites they explore. In this article, we will present an innovative chatbot-based system, called HeriBot, that supports experiential tourism. Our system has been developed and experimented with a research effort for applying ICT technologies to enhance the knowledge, valorization, and sustainable fruition of the Cultural Heritage related to the Archaeological Urban Park of Naples (PAUN—Parco Archeologico Urbano di Napoli). Our article starts exploiting the ontological approach based on a purpose ontology describing the Park Heritage. Using such an ontology, we designed a chatbot that can identify the specific characteristics and motivations of the tourist, defining language, tone, and visitable scenarios and, through the ontology, allows the visit to be transformed into a personalized educational opportunity. The system has been validated in terms of dialogue effectiveness and training efficiency by a panel of experts, and we present and discuss obtained results.

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Ontologies for the classification of cultural heritage data

Cited by 8 publications

References 14 publications

Hybrid recommender system for tourism based on big data and AI: A conceptual framework

Hybrid recommender system for tourism based on big data and AI: A conceptual framework

Towards an Integrated Platform for the Presentation and Preservation of the Scientific Heritage of Drâa-Tafilalet

An Ontology-Based Chatbot to Enhance Experiential Learning in a Cultural Heritage Scenario

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