3,442 Results Found

Algorithmic personalization is the flagship mechanism of interactive marketing: platforms learn from user behavior and respond with individually curated value propositions, and industry practice treats the quality of that loop as a lever for customer...

Personalized travel itinerary recommendation algorithms are the focus of research in smart tourism and tourism GIS. Aiming to address issues present in travel itinerary recommendations for the increasingly popular “self-drive tour” mode,...

In this era of intelligence, the learning methods of learners have substantially changed. Many learners choose to learn through online education platforms. Although learners may enjoy more high-quality educational resources, when they are faced with...

(1) Background: Problematic social media use has increasingly been conceptualized as a non-clinical addictive-like behavior characterized by impaired control and negative functional consequences. Despite the rapid growth of TikTok and its algorithm-d...

Integrated learning can be used to combine weak classifiers in order to improve the effect of emotional classification. Existing methods of emotional classification on micro-blogs seldom consider utilizing integrated learning. Personality can signifi...

The use of TikTok is more widespread now than ever, and it has a big impact on users’ daily lives, with self-perceived identity and personal values being topics of interest in light of the algorithmically curated content. This mini-review summa...

To solve the problems of slow convergence and low accuracy when the traditional ant colony optimization (ACO) algorithm is applied to online learning path recommendation problems, this study proposes an online personalized learning path recommendatio...

With the explosive growth of the amount of information in social networks, the recommendation system, as an application of social networks, has attracted widespread attention in recent years on how to obtain user-interested content in massive data. A...

This study examines how consumers respond to personalized advertisements that appear to be derived from prior conversations with generative AI assistants in social commerce settings. Drawing on the Privacy Calculus Theory, Trust Theory, and the Stimu...

The aim of this study is to present an integrated approach to ski personalization by combining a detailed material and geometric characterization of ski structure with real-time on-slope dynamic performance data. Longitudinal and torsional stiffness...

The probability of losing vulnerable companions, such as children or older ones, in large gatherings is high, and their tracking is challenging. We proposed a novel integration of face-recognition algorithms with a soft voting scheme, which was appli...

The planning of the surgical treatment in orthopedics, with the help of three-dimensional (3D) technologies, arouses an increasing scientific interest. Scientific literature describes some semi-automatic reconstructive attempts at fragmented bone fra...

Defining a passenger’s thermal comfort in a car cabin is difficult because of the narrow environment and various parameters. Although passenger comfort is predicted using a thermal-comfort scale in the overall cabin or a local area, the scale&r...

In the realm of personalized federated learning, some current methods substitute shared parameters with shared samples created by Generative Adversarial Networks (GANs). This enables each client to independently design the architecture of their neura...

Artificial intelligence (AI)-powered personalized recommendation systems can enhance relevance and convenience, but their reliance on extensive personal data processing may also heighten users’ perceptions of privacy intrusion. This study exami...

To alleviate the emission of greenhouse gas and the dependence on fossil fuel, Plug-in Hybrid Electrical Vehicles (PHEVs) have gained an increasing popularity in current decades. Due to the fluctuating electricity prices in the power market, a chargi...

News recommending systems (NRSs) are algorithmic tools that filter incoming streams of information according to the users’ preferences or point them to additional items of interest. In today’s high-choice media environment, attention shif...

This study investigated the relationship between personality states and driving behavior from a dynamic perspective. A personality baseline was introduced to reflect the driver’s trait level and can be used as a basic reference for the dynamic...

This paper addresses the challenge of objectively determining a website’s personality by developing a methodology based on automated quantitative analysis, thus avoiding the biases inherent in human surveys. Utilizing a database of 3000 website...

This study investigates personalized pricing with demand learning. We first encode consumer-personalized feature information into high-dimensional vectors, then establish the relationship between this feature vector and product demand using a logit m...

Technological advancements in algorithmic personalization are widely believed to influence user behavior on online gambling platforms. This study explores how such developments, potentially including AI-driven mechanisms, may affect cognitive and mot...

In the context of the Internet, the personalization and diversification of customer demands present a significant challenge for research on the identification, combination, and utilization of personalized demand feature elements. A key difficulty lie...

This study examines the complex dynamics of advertising avoidance in the social media context, with particular emphasis on the roles of psychological reactance perceived surveillance, privacy concerns, and algorithmic fatigue. It delineates the intri...

The IoT is a specific type of network with its own communication challenges. There are a multitude of low-power devices monitoring the environment. Thus, the need for authentication may be addressed by many available sensors but should be performed o...

Modern workplaces increasingly use algorithmic management practices (AMPs), which shape task assignment, monitoring, and evaluation. Despite the potential benefits these practices offer, like increased efficiency and objectivity, their impact on work...

Social networks have increasingly become important and popular in modern times. Moreover, the influence of social networks plays a vital role in various organizations, including government organizations, academic research organizations and corporate...

Artificial intelligence (AI) is transforming fashion e-commerce through personalized recommendations, virtual try-on, size suggestions, and algorithmic decision support. This study examines AI-driven fit confidence as a fashion-specific mechanism lin...

Personalized search and recommendation algorithms for multi-modal data have attracted widespread attention. However, existing methods often struggle with effectively integrating multi-source information and performing global search in complex optimiz...

A significant challenge for a supervised learning approach to inertial human activity recognition is the heterogeneity of data generated by individual users, resulting in very poor performance for some subjects. We present an approach to personalized...

Addressing the problems facing the elderly, whether living independently or in managed care facilities, is considered one of the most important applications for action recognition research. However, existing systems are not ready for automation, or f...

Considering that group formation is key when developing activities in collaborative learning scenarios, this paper aims to propose a strategy based on a genetic algorithm approach for achieving optimal collaborative learning groups, considering the s...

In this paper, an approach based on genetic algorithms is proposed to form groups in collaborative learning scenarios, considering the students’ personality traits as a criterion for grouping. This formation is carried out in two stages: In the first...

The traditional heterogeneous embedding method based on a random walk strategy does not focus on the random walk fundamentally because of higher-order Markov chains. One of the important properties of Markov chains is stationary distributions (SDs)....

Precision medicine entails the design of therapies that are matched for each individual patient. Thus, predictive modeling of drug responses for specific patients constitutes a significant challenge for personalized therapy. In this article, we consi...

In the field of financial investment, accurate prediction of financial market values can increase investor profits. Investor personality affects specific portfolio solutions, which keeps them symmetrical in the process of investment competition. Howe...

Thermal comfort and sensation are important aspects of building design and indoor climate control, as modern man spends most of the day indoors. Conventional indoor climate design and control approaches are based on static thermal comfort/sensation m...

Chronic diseases are a significant healthcare problem. Partial or complete non-responsiveness to chronic therapies is a significant obstacle to maintaining the long-term effect of drugs in these patients. A high degree of intra- and inter-patient var...

In this work, a method for automatic hyper-parameter tuning of the stacked asymmetric auto-encoder is proposed. In previous work, the deep learning ability to extract personality perception from speech was shown, but hyper-parameter tuning was attain...

Exoskeletons offer promising solutions for enhancing human mobility; however, personalizing assistance parameters to optimize physiological outcomes remains challenging. Human-in-the-loop (HIL) optimization has emerged as an effective strategy for ta...

Nowadays, the demand for more personalized healthy food recipes is increasing over time, but traditional personalized recipe recommendation systems often tend to overlook the differences that exist in different users’ health conditions. This pa...

By shining a light on the previously neglected combination of public service media (PSM) and the audience perspective, this paper adds to the debate on (algorithmic) news personalization. While news personalization may offer new opportunities, it can...

Person re-identification has become an essential application within computer vision due to its ability to match the same person over non-overlapping cameras. However, it is a challenging task because of the broad view of cameras with a large number o...

Feedback is a crucial component of effective, personalized learning, and is usually provided through formative assessment. Introducing formative assessment into a classroom can be challenging because of test creation complexity and the need to provid...

Mobile activity recognition is significant to the development of human-centric pervasive applications including elderly care, personalized recommendations, etc. Nevertheless, the distribution of inertial sensor data can be influenced to a great exten...

The success of software projects is inseparable from the effective scheduling of multi-skilled human resources. In software development, employees’ personality traits often affect the performance of their work. Additionally, software developers...

With an increased number of medical data generated every day, there is a strong need for reliable, automated evaluation tools. With high hopes and expectations, machine learning has the potential to revolutionize many fields of medicine, helping to m...

Acute Myeloid Leukemia (AML) is a heterogeneous group of aggressive blood-related cancers that arise from the hematopoietic system, requiring specific treatments due to their genetic diversity and complexity. Artificial intelligence (AI) has emerged...

Falls account for about one-third of all construction fatalities with most fatalities in the roofing trade. Even though a personal fall arrest system (PFAS) is required for fall protection, proper placement of PFAS anchor points is an issue evidenced...

It is not easy to find learning materials of interest quickly in the vast amount of online learning materials. The purpose of this study is to find students’ interests according to their learning behaviors in the network and to recommend relate...

The development of a carbon-neutral production and distribution method that minimizes the consumption of input resources and energy and facilitates resource recycling is an important global issue. Therefore, this study aimed to explore a new type of...