The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to tran...
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The software development process mostly depends on accurately identifying both essential and optional ***,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional *** address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human ***,existing techniques often struggle with complex instructions and large-scale *** our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer *** results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT *** datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse *** findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.
Thailand has a wide variety of tourist attractions, making it difficult for tourist to choose where to go on vacation. The tourist destination recommendation system is a challenge for creating a system to help recomme...
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data scarcity in low-resource languages can be addressed with word-to-word translations from labeled task data in high-resource languages using bilingual lexicons. However, bilingual lexicons often have limited lexica...
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This paper investigates the 3D domain generalization (3DDG) ability of large 3D models based on prevalent prompt learning. Recent works demonstrate the performances of 3D point cloud recognition can be boosted remarka...
Blockchain is a distributed database that multiple parties can maintain and share. This new technology is expected to greatly impact the healthcare industry. It can help address various issues related to patient care....
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Recent works often assume that Vision-Language Model (VLM) representations are based on visual attributes like shape. However, it is unclear to what extent VLMs prioritize this information to represent concepts. We pr...
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Artificial intelligence (AI) advancements have opened new avenues in medical diagnostics, particularly for the early detection of respiratory conditions such as Chronic Obstructive Pulmonary Disease (COPD). COPD, the ...
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In banking, maintaining customer retention and customer satisfaction are important. Effective customer segmentation can be a strategic tool to improve customer loyalty and business performance. This research can assis...
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Artificial intelligence (AI) breakthroughs have created new opportunities in the field of medical diagnostics, especially for the early identification of respiratory conditions like Chronic Obstructive Pulmonary Disea...
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Graph neural networks (GNNs) have shown outstanding performance in graph node classification. However, as a deep learning model, GNNs can be influence by adversarial attacks, such as graph injection attacks or graph m...
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