Ontology-Based Recommender System for Sport Events

Nguyen, Quang; Huynh, Luan N. T.; Le, Tuyen P.; Chung, T. J.

doi:10.1007/978-3-030-19063-7_69

Cited by 10 publications

(4 citation statements)

References 11 publications

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“…Sánchez et al [46] defined the optimal structure of the Australian economy by maximizing GDP and employment and minimizing greenhouse gas emissions. Nguyen et al [47] determined the ideal structure of Vietnam with the minimization of the carbon emissions and the energy consumption and the maximization of GDP. In the case of Greece, three different studies provide evidence for its optimal structure: Hristu-Varsakelis et al [48] explored different scenarios based on GDP maximization and energy conservation to determine the optimal structure of the country.…”

Section: Optimizing the Impact Industrial Policy: A Methodological Approachmentioning

confidence: 99%

A Modern Industrial Policy for the Czech Republic: Optimizing the Structure of Production

2021

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The decreased demand for new vehicles will put pressure on the economy of the Czech Republic, a country deeply integrated into global value chains, as part of global vehicle production. The aim of this research was to define an appropriate industrial policy for the Czech Republic that will ensure that the country maintains its competitive position in the global market. A constrained optimization model was built, based on input–output analysis, to determine the optimal value-added structure and the intersectoral structure of the Czech economy for the country to retain its exporting character. The optimization problem was solved by using a particle swarm optimization algorithm. The results suggest that the optimal industrial policy plan for the country is the structural transformation of production, mainly targeting the development of technologically advanced sectors of manufacturing (such as: chemicals and chemical products; basic pharmaceutical products; computer, electronic, and optical products; electrical equipment; and machinery and equipment). The suggested restructuring process increased the domestic value-added in gross exports as a share of total exports by 6.77%, creating optimal production capabilities for the economy. The Czech Republic appears to have the potential for the implementation of an industrial policy, avoiding the increasingly vulnerable motor-vehicle sector.

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Section: Optimizing the Impact Industrial Policy: A Methodological Approachmentioning

confidence: 99%

A Modern Industrial Policy for the Czech Republic: Optimizing the Structure of Production

2021

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“…CF recommenders support serendipity effects, i.e., a sports event recommender would not just focus on the current user preferences but potentially identify events of further interest not directly related to the current preferences. In contrast, content-based filtering would focus on very similar events [4,90], for example, a marathon runner who participated in marathons in New York and Boston up-to-now would receive related recommendations of future events, including, for example, other marathon events in the US. Case-based, more precisely, critiquing-based recommender systems [25] can help to navigate and better understand the whole item space and -if the corresponding data is available -help to efficiently narrow down the option space, for example, only events should be recommended, where opponents participate who have a similar competitive level as the "current user".…”

Section: Sports Eventsmentioning

confidence: 99%

Sports Recommender Systems: Overview and Research Issues

Felfernig,

Wundara,

Tran

et al. 2023

Preprint

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Sports recommender systems receive an increasing attention due to their potential of fostering healthy living, improving personal well-being, and increasing performances in sport. These systems support people in sports, for example, by the recommendation of healthy and performance-boosting food items, the recommendation of training practices, talent and team recommendation, and the recommendation of specific tactics in competitions. With applications in the virtual world, for example, the recommendation of maps or opponents in e-sports, these systems already transcend conventional sports scenarios where physical presence is needed. On the basis of different working examples, we present an overview of sports recommender systems applications and techniques. Overall, we analyze the related state-of-the-art and discuss open research issues.

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“…Quang Nguyen et al constructed a recommendation system for sport events with natural language processing and unsupervised learning methods. To realize this function, the ontological framework and user characteristics are constructed by collecting data from online sports sites [ 37 ]. Rule-based systems have been extensively used in several applications and domains.…”

Section: Related Workmentioning

confidence: 99%

Knowledge graph of alpine skiing events: A focus on meteorological conditions

et al. 2022

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Alpine skiing, as an outdoor winter sport, is particularly vulnerable to the variation of meteorological conditions. Scattered and multi-source big data cannot be fully utilized to conduct effective decision analyses by conventional data analysis methods. Presently, knowledge graphs are the most advanced organization form of knowledge base, which can make explicit the complex relationships among different objects. Thus, introducing knowledge graph to the event management of alpine skiing is significant to improve the ability of risk prediction and decision-making. In this research, we analyze the components and dynamic characteristics of alpine skiing, and construct an “Object-Characteristic-Relation” representation model to express multi-level knowledge. Moreover, we propose a “Characteristic-value- Relationship” representation method based on the multi-source data, to construct the knowledge graph of alpine skiing. With the proposed method, comprehensive relationships between meteorological conditions and alpine skiing can be represented clearly, and support further knowledge reasoning for the event management under meteorological conditions. We have tested the utility of the proposed method in a case study of 2018 Winter Olympics in PyeongChang. The case study realizes an semi-automatic construction of knowledge graph for alpine skiing, provides decision supports for event risk managements, according to different meteorological conditions, and grounds a foundation for future knowledge graph construction of other large-scale sport events.

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Ontology-Based Recommender System for Sport Events

Cited by 10 publications

References 11 publications

A Modern Industrial Policy for the Czech Republic: Optimizing the Structure of Production

A Modern Industrial Policy for the Czech Republic: Optimizing the Structure of Production

Sports Recommender Systems: Overview and Research Issues

Knowledge graph of alpine skiing events: A focus on meteorological conditions

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