The company also facilitates the exchange of car-related information, such as advertisement, second-hand car selling, and remodeling, to build a car-related information platform. The app owner has focused on the total user experience, offering a friendly and smooth user interface. The app collaborates with well-known car media, websites, and magazines, providing users with more than 100 car news and market dynamics every month to ensure comprehensive and real-time news exposure. The app was launched in December 2013, providing users with comprehensive information on cars, including details, specifications, a media database with high-quality photos and videos, and up to 20 test drive reports every month. The data include 30,867 vehicle comparisons from 5327 users across 40 car brands and 870 cars from 30 January 2015 to 2 April 2015. This study employs pairwise comparison records from Taiwan’s New Cars Database mobile app. Lastly, customization with social influence and explicit feedback refers to a recommendation system personalized to the user’s past behavior, relationships with other people, and the user’s explicit feedback on the items they have tried and tested. Customization with social influence refers to a recommendation system that is personalized to the user’s past behavior and considers the user’s relationships with others. Customization refers to a recommendation system personalized to the user’s past behavior. There are three levels of personalization in recommendation systems: customization, customization with social influence, and customization with social influence and explicit feedback. Therefore, one way of categorizing recommendation systems is to look at the level of personalization, the extent to which a recommendation system is tailored to the individual user or the extent to which a recommendation system is tailored to the individual user. Personalized recommendations are based on the individual’s unique characteristics, whereas non-personalized recommendations are based on a larger data set. One of the most important challenges in recommendation systems is deciding whether to customize recommendations for a particular user or to make non-personalized recommendations that are more general. The proposed hybrid approach aims to provide more reliable and comprehensive product recommendations by combining both approaches and has implications for both academic and managerial contexts by facilitating the development of effective recommendation systems. In addition, the unit of analysis can affect the recommendation system’s output, with comparison lists supplementing and expanding the exploration of potential outcomes. The findings suggest that adjusting the support and confidence values can improve the breadth and depth of product recommendations. Two metrics are developed to measure the system’s output under varying support and confidence thresholds. The study employs a dataset from the New-Cars Database app, comprising 30,867 vehicle comparisons made by 5327 users across 40 car brands and 870 cars from 30 January 2015 to 2 April 2015. This study proposes a hybrid approach that utilizes comparative facts from pairwise comparison data and comparison lists, with association rules as the method to formulate the recommendation system. This was the third event to be held at CERN, the two previous ones having taken place in 20.Īll the photos from the event can be found here.Product recommendation systems are essential for enhancing customer experience, and integrating them with mobile apps is crucial for improving usability and fostering user engagement. Some 450 events have been held so far worldwide, reaching more than 8000 children. The DevoXX4Kids initiative was launched in 2012 with the aim of providing, developing and bringing together tools and running workshops to familiarise children and teenagers with programming and IT systems in a fun way. The Teens (aged 11–15) spent the day at IdeaSquare, where they learned about the electronics of the Internet of Things, robotics using the Poppy Ergo Jr, Thymio and Bitbot:XL robots, and HyperText Markup Language (HTML). In the afternoon session, the Kids (aged 7–10) were introduced to coding using CodeCombat and made their own video games using the Kids-lab.io platform. In the morning session, at the Globe of Science and Innovation, the Minis (aged 4–6) discovered the basics of screen-free programming, thanks to the Cubetto robot and the board game Robot Turtles. Around a hundred children aged between 4 and 15 took part in the event. On Saturday, 11 March 2023, CERN hosted DevoXX4Kids – a day of workshops dedicated to programming, robotics and electronics.
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