The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Background & Aims
Short videos, crucial for disseminating health information on metabolic dysfunction‐associated steatotic liver disease (MASLD), lack a clear evaluation of quality and reliability. This study aimed to assess the quality and reliability of MASLD‐related videos on Chinese platforms.
Methods
Video samples were collected from three platforms (TikTok, Kwai and Bilibili) during the...
Thermocline has a significant impact on marine fishery, navy submarine activity, ocean circulation and internal wave. In consideration of long range, low cost, and high maneuverability, the AUV (Autonomous Underwater Vehicle) is an ideal platform for ocean local precisely thermocline tracking. Combining with the advantage of the AUV yo-yo movement, this paper presents a simple and effective thermocline...
Traditional User-based collaborative filtering recommendation algorithm in the calculation of similarity between users only considers the users' score to the item, but not takes the difference of rated items into account. Aiming at the shortcomings of the traditional method, with the practical application of recommendation system, a new collaborative filtering recommendation algorithm is proposed...
Aiming at the shortcomings of datasets sparsity and cold start in the traditional Item-based collaborative filtering recommendation algorithm, to improve the calculating accuracy of similarity and recommendation quality, taking attribute theory as theoretical basis, a collaborative filtering recommendation algorithm based on item attributes is proposed. Through analyzing the items, the attributes...
Collaborative filtering technology is the mainstream recommendation technology in personalized recommendation system, the sparsity of the dataset plays a leading role in the prediction accuracy of the collaborative filtering algorithm. Virtual data filling and neighbors' calculation etc. are adopted to solve the sparsity problem in traditional methods, which lacked of dynamic changes of rating data...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.