In sports, a team or athlete may feel they have momentum, or "power/strength" during a game, but this phenomenon is difficult to measure. Furthermore, it is not clear how various events during a match create...
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Electronic devicerecommendations on e-commerce sites enhance the user experience by assisting users in finding products that suit their requirements, interests, and preferences. By providing them with pertinent option...
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ISBN:
(纸本)9798331540364
Electronic devicerecommendations on e-commerce sites enhance the user experience by assisting users in finding products that suit their requirements, interests, and preferences. By providing them with pertinent options, it helps users who are looking for specific gadgets save time and effort. Electronic devices commonly saw shorter product lifecycles due to the regular introduction of updated and new models. Users may feel under pressure to update to newer versions in order to access the newest features or upgrades, which could cause obsolescence problems. Previously NLP techniques are utilized for recommending electronic gadgets. Biased recommendations may result from NLP models inheriting biases found in the training set of data. As a result, there may be unfair or discriminatory consequences, such as more product recommendations for particular demographic groups or the reinforcement of preexistingpreconceptions. GPT may be used to construct chatbots or AIs that engage with customers using natural language. These assistance systems driven by AI are able to help customers make purchases, answer their questions, and make personalized product suggestions. Companies can improve the customer experience by responding quickly and giving useful information. One can use GPT to simplify customer service tasks like answering common questions and fixing problems right away. This can help companies help customers around the clock, speed up reaction times, and give human support workers less work to do. Support systems driven by GPT can also learn from exchanges with customers over time, making them better at what they do. High-quality material may be produced by GPT for use in blog entries, social media postings, marketingand copy, including product descriptions. One can use this material to get people interested in and buying from your e-commerce sites, show off product attributes and advantages, and attract new customers. We can also make GPT-generated content search engine
In response to the escalating impact of the greenhouse effect on Earth's climate, electric vehicles (EVs) have emerged as a pivotal solution for sustainable transportation. This research addresses a critical chall...
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An image encryption algorithm is proposed in this paper based on a new four-dimensional hyperchaotic system,a neural mechanism,a Galois field and an improved Feistel block structure,which improves the efficiency and e...
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An image encryption algorithm is proposed in this paper based on a new four-dimensional hyperchaotic system,a neural mechanism,a Galois field and an improved Feistel block structure,which improves the efficiency and enhances the security of the encryption ***,a four-dimensional hyperchaotic system with a large key space and chaotic dynamics performance is proposed and combined with a cloud model,in which a more complex and random sequence is constructed as the key stream,and the problem of chaotic periodicity is ***,the key stream is combined with the neural mechanism,Galois field and improved Feistel block structure to scramble and diffuse the image ***,the experimental results and security analysis show that the encryption algorithm has a good encryption effect and high encryption efficiency,is secure,and can meet the requirements of practical applications.
The next POI recommendation plays a significant role in location-based services because it provides personalized suggestions for destinations to users. The most advanced research utilizes enhanced attention mechanisms...
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To address the issue of low intrusion detection accuracy due to incomplete feature extraction by a single model, an SS-CBLM model detection method is proposed. This method combines Convolutional Neural Networks (CNN) ...
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Artificial Intelligence Generated Content (AIGC) services can efficiently satisfy user-specified content creation demands, but the high computational requirements pose various challenges to supporting mobile users at ...
Deep Learning (DL)-based models have been successfully applied for medical image classifications. However, the performance of traditional medical image classifiers is limited by insufficient training samples and inacc...
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Due to the growing number of automobiles on the road, there is a significant increase in demand for parking spots in metropolitan areas. Therefore, motorists constantly struggle to find good parking spots. Moreover, t...
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The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare *** is to make sure that decisions are based on trustworthy algorithms and that healthc...
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The use of Explainable Artificial Intelligence(XAI)models becomes increasingly important for making decisions in smart healthcare *** is to make sure that decisions are based on trustworthy algorithms and that healthcare workers understand the decisions made by these *** models can potentially enhance interpretability and explainability in decision-making processes that rely on artificial ***,the intricate nature of the healthcare field necessitates the utilization of sophisticated models to classify cancer *** research presents an advanced investigation of XAI models to classify cancer *** describes the different levels of explainability and interpretability associated with XAI models and the challenges faced in deploying them in healthcare *** addition,this study proposes a novel framework for cancer image classification that incorporates XAI models with deep learning and advanced medical imaging *** proposed model integrates several techniques,including end-to-end explainable evaluation,rule-based explanation,and useradaptive *** proposed XAI reaches 97.72%accuracy,90.72%precision,93.72%recall,96.72%F1-score,9.55%FDR,9.66%FOR,and 91.18%*** will discuss the potential applications of the proposed XAI models in the smart healthcare *** will help ensure trust and accountability in AI-based decisions,which is essential for achieving a safe and reliable smart healthcare environment.
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