ACUX Recommender: A Mobile Recommendation System for Multi-Profile Cultural Visitors Based on Visiting Preferences Classification

Konstantakis, Markos; Christodoulou, Yannis; Aliprantis, John

doi:10.3390/bdcc6040144

Cited by 17 publications

(10 citation statements)

References 32 publications

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“…In Konstantakis et al (2022), the authors propose the ACUX recommendation system, in order to recommend POIs to visitors in a personalized manner. The proposed recommendation system replies on a collection of typologies in order to assign the visitors to one or more out of the eight available ACUX profiles.…”

Section: Related Workmentioning

confidence: 99%

“…Since many tourists rely heavily on their mobile devices to enhance their travel experiences, the development of personalized mobile applications has become increasingly important. These applications offer targeted recommendations for POIs at a visiting site, which ultimately improve the cultural experience for the user Tenemaza et al (2020); Kashevnik et al (2019); Konstantakis et al (2022); Missaoui et al (2019); Kenteris et al (2009). This is particularly crucial for visitors who may have short stays in several locations, such as cruise ship tourists.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Visit Planner: A Personalized Mobile Trip Design Application based on a Hybrid Recommendation Model

Papadakis

Panagiotakis

Fragopoulou

et al. 2023

Preprint

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The paper presents Visit Planner (ViP), a mobile application prototype that provides a solution to the challenging tourist trip design problem. ViP follows a holistic approach offering personalized recommendations for Points of Interest (POIs) based on preferences either explicitly collected by the application, or inferred by the users’ ongoing interaction with the system. ViP proposes to the final user, a trajectory of POIs calculated using an Expectation Maximization method that maximizes user satisfaction taking into consideration a variety of time and spatial constraints for both users and POIs. Additionally, POIs are divided into categories, so that a certain number of POIs from each category to be included in the final itinerary. The application is implemented as a user-interactive system that allows the flexibility for easy content adaptation and facilitates management of content and services by the user.The prototype has been implemented for Android-based smartphones, on an open application environment, using standard communication protocols and open database technology. Currently, it is applied to the city of Agios Nikolaos in Crete, and is available for download from Google play. MSC Classification: 68T20 , 68N99

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Visit Planner: A Personalized Mobile Trip Design Application based on a Hybrid Recommendation Model

Papadakis

Panagiotakis

Fragopoulou

et al. 2023

Preprint

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“…Another interesting future study area may involve personalization over the application. Different personas may be interested in different points of view and POIs, for which a recommender system [32] may be employed for further personalization according to the user's taste and interest [33].…”

Section: Future Workmentioning

confidence: 99%

Utilizing Stereography to Compare Cultural Heritage in the Past and Now: An Interactive AR Application

Bolognesi,

Sorrenti,

Bassorizzi

2023

Applied Sciences

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Due to the astonishing speed in technological progress for new heterogeneous experiences, the Mixed Reality continuum represents nowadays an invaluable tool for cultural heritage applications, and the possibility of seemingly natural interaction with virtual elements is paving the way for more immerse, ve and deeply enjoyable experiences, both in dedicated spaces, such as museums and exhibitions, and in public spaces via the latest mobile AR technologies. This paper illustrates the complete workflow followed for the design and implementation of an Augmented Reality application on a holographic table, along with critical latency-quality tradeoffs encountered when combining both high-fidelity surveys and latency-sensibility devices and experiences. A workaround is provided in order to mitigate the impact of low-importance models on the overall latency utilizing a software toolchain employing Google Maps/Earth web applications; each software comprises the toolchain Free and Open-Source Software (FOSS) for a more adaptive workaround with a wider range of suitable applications. The application is then tested with the students of LaborA, which is the modeling laboratory of “Politecnico di Milano”.

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“…Nevertheless, the algorithm was developed considering the ratings only, which could not be reliable since some popular places receive lower ratings. [21] presented a mobile RS for multi-profile cultural visitors grounded on visiting preferences classification named ACUX Recommender (ACUX-R). To assign profiles for cultural visitors, ACUX topology was leveraged.…”

Section: Related Workmentioning

confidence: 99%

Developing an MQ-LSTM-Based Cultural Tourism Accelerator with Database Security

Jeribi,

Ahamed,

Perumal

et al. 2023

Sustainability

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Cultural tourism (CT), which enhances the economic development of a region, aids a country in reinforcing its identities, enhancing cross-cultural understanding, and preserving the heritage culture of an area. Designing a proper tourism model assists tourists in understanding the point of interest without the help of a local guide. However, owing to the need for the analysis of different factors, designing such a model is a complex process. Therefore, this article proposes a CT model for peak visitor time in Riyadh, a city in Saudi Arabia. The main objective of the framework is to improve the cultural tourism of Riyadh by considering various factors to help in improving CT based on recommendation system (RS). Primarily, the map data and cultural event dataset were processed for location, such as grouping with Kriging interpolation-based Chameleon (KIC), tree forming, and feature extraction. After that, the event dataset’s attributes were processed with word embedding. Meanwhile, the social network sites (SNS) data like reviews and news were extracted with an external application programming interface (API). The review data were processed with keyword extraction and word embedding, whereas the news data were processed with score value estimation. Lastly, the data were fused, corresponding to a historical site, and given to the Multi-Quadratic-Long Short-Term Memory (MQ-LSTM) recommendation system (RS); also, the recommended result with the map was stored in a database. Lastly, the database security was maintained with locality sensitive hashing (LSH). From the experimental evaluation with multiple databases including the Riyadh Restaurants 20K dataset, the proposed recommendation model achieved a recommendation rate (RR) of 97.22%, precision of 97.7%, recall of 98.27%, and mean absolute error (MAE) of 0.0521. This result states that the proposed RS provides higher RR and reduced error compared to existing related RSs. Thus, by attaining higher performance values, the proposed model is experimentally verified.

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ACUX Recommender: A Mobile Recommendation System for Multi-Profile Cultural Visitors Based on Visiting Preferences Classification

Cited by 17 publications

References 32 publications

Visit Planner: A Personalized Mobile Trip Design Application based on a Hybrid Recommendation Model

Visit Planner: A Personalized Mobile Trip Design Application based on a Hybrid Recommendation Model

Utilizing Stereography to Compare Cultural Heritage in the Past and Now: An Interactive AR Application

Developing an MQ-LSTM-Based Cultural Tourism Accelerator with Database Security

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