Run-time monitoring has been one of the widely used techniques to realize robust smart contracts. In this paper, we show how we can abstract aspects of run-time monitoring through declarations of programming languages...
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Diabetes is a common disease that causes complications in the eyes known as Diabetic Retinopathy (DR). It aids in discovering the DR and tends to be the main cause behind people’s blindness amidst the previous decade...
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During the last three decades, the importance of the application software is tremendously increased. Every organization has automated all their day-to-day activities. For automation purpose they used the procedural or...
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This study introduces an innovative framework for predicting diabetes, employing advanced imputation strategies and ensemble machine learning techniques to boost prediction accuracy. Given the irreversible nature of d...
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Memory bandwidth and power consumption is of utmost importance in the design of low power edge devices. This makes it essential to conserve power both at the sensor node and the computational unit. Our paper proposes ...
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Plant disease detection is important for several reasons, such as forecasting crop loss, tracking and forecasting infections, identifying host resistance, and researching fundamental biological interactions between ho...
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Lung illness is any condition that impairs the lungs' capacity to function normally;diabetes, in particular, can have a variety of effects on the lungs and increases the risk of respiratory infections such as pneu...
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Software-defined networking (SDN) is a transformative technology that systematically centralises and manages network resources. This paradigm shift allows for greater flexibility, agility, and efficiency in network ma...
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Even though every individual is entitled to freedom of speech, some limitations exist when this freedom is used to target and harm another individual or a group of people, as it translates to hate speech. In this stud...
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In today’s information-rich digital age, the volume of web content available to users has become overwhelming, making it challenging for individuals to find relevant and personalized content. Recommendation systems h...
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ISBN:
(纸本)9789819747108
In today’s information-rich digital age, the volume of web content available to users has become overwhelming, making it challenging for individuals to find relevant and personalized content. Recommendation systems have emerged as a transformative solution, catering to individual users by offering customized suggestions aligned with their unique interests. This research explores a novel approach that utilizes topic modeling techniques on web content titles for recommendation purposes. Topic modeling, a subfield of natural language processing (NLP) is utilized to automatically identify latent topics within a large corpus of text. The proposed work begins by collecting a diverse dataset of web content titles across the domains. It employs a combination of other state-of-the-art topic modeling algorithms like BERTopic modeling and statistical model to uncover the underlying topics in the titles. By leveraging this approach on web content titles, aim to extract meaningful themes and categorize the content efficiently. Then preprocess the data to remove irrelevant information, ensuring that the subsequent topic modeling process yields accurate and meaningful results. This approach not only expedites the recommendation process but also conserves computational resource. Once the topics are identified, associate them with appropriate metadata, such as user preferences, and content types. This step forms the foundation of our content-based recommendation approach. Then maps the user’s interests to the most relevant topics, enabling us to present a tailored list of web content titles. By recommending content based on underlying themes rather than just keywords, this approach surpasses traditional methods, ensuring more accurate and diverse suggestions for users. The results demonstrate the system’s ability to provide highly personalized recommendations, enhancing user satisfaction and engagement. By delving into the semantic structure of content rather than relying solely on
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