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31 articles for “Term extraction”

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Research ArticleOpen accessPhrase in the titleImproving Term Extraction Using Particle Swarm Optimization TechniquesMohammad Syafrullah, Naomie SalimProblem statement: Term extraction is one of the layers in the ontology development process which has the task to extract all the terms contained in the input document automatically. The purpose of this process is to generate list of terms that are relevant to the domain of the input document. In the literature there are many approaches, techniques and algorithms … …Journal of Computer Science, Vol. 6, Issue 3 · 31 Mar 2010 · 7,138 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSentence Annotation based Enhanced Semantic Summary Generation from Multiple DocumentsA. Kogilavani, P. BalasubramanieProblem statement: The goal of document summarization is to provide a summary or outline of manifold documents with reduction in time. Sentence extraction could be a technique that is employed to pick out relevant and vital sentences from documents and presented as a summary. So there is a need to develop more meaningful sentence selection strategy so as to extract … …American Journal of Applied Sciences, Vol. 9, Issue 7 · 17 May 2012 · 7,001 accessesView PDFCite
Research ArticleOpen accessIn the abstractGait Analysis Combining Sports Biomechanics and ImagingChao ZhuAiming at the problems of marker positioning error, soft tissue interference, and insufficient personalized modeling ability in traditional gait analysis, this study proposes a gait assessment method that integrates sports biomechanics and multimodal imaging analysis. Firstly, based on the public OU-ISIR gait database, a Convolutional Neural Network (CNN) is used to extract the key gait features in the human silhouette … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 20 Jul 2026 · 850 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Dynamic Lifelong Learning Network for Real-Time Stock Prediction With Reinforcement TuningTalent Mawere, Selvaraj Rajalakshmi, Venu Madhav Kuthadi, Otlhapile DinakanyaneCompanies and investors require accurate market forecasting to make more informed decisions. Traditional methods for predicting stock market performance have become less useful considering the dynamic and volatile nature that characterizes stock markets today. In this paper, we propose an innovative Dynamic Lifelong Learning Network for stock market prediction. The model incorporates a hybrid convolutional long short-term memory with an … …Journal of Computer Science, Vol. 22, Issue 2 · 20 Feb 2026 · 1,822 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning Synergy: CNNs and Transformers for Epidemic Outbreak ForecastingAlexander R., Shakthi Priya V., Sumathi G. et al.An Accurate prediction of outbreaks is extremely crucial for taking proactive public health interventions, distributing limited resources, and controlling a disease. This paper assesses and also compares the performances of the available deep learning models, namely, Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) networks, and Bidirectional Long Short-Term Memory (BiLSTM) networks, in predicting. CNNs are best for feature extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,113 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,395 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Combined Deep Learning Model with Attention Mechanism for Detection of Implant Manufacturer Using X-Ray ImagesAttar Mahay Sheetal, K. SreekumarShoulder replacement surgery is one of the invasive techniques in orthopedic disciplines that replaces dead shoulder joints with prostheses made from polyethylene and metal components. To perform the surgery, there is a need to know the implant accessories and manufacturer of the implant. Some problems arise in a situation where the patient experiences pain and shoulder malfunctions that need replacement, … …Journal of Computer Science, Vol. 21, Issue 6 · 12 Jun 2025 · 3,252 accessesView PDFCite
Research ArticleOpen accessIn the abstractOnline Handwritten Physics Expression Recognition Using a CRNN-LSTM ApproachUjwala Pritam Kolte, Sachin Arun NaikOptical Character Recognition (OCR) is crucial for identifying and extracting information from scientific documents. However, recognizing online handwritten physics expressions remains a relatively unexplored area of research. In the existing literature, most of the researchers worked on CNN classification to identify mathematical expressions. The traditional Convolution Neural Network (CNN) has limitations for extracting sequential data. This study proposes a CRNN … …Journal of Computer Science, Vol. 21, Issue 2 · 31 Dec 2024 · 4,812 accessesView PDFCite
Research ArticleOpen accessIn the abstractMeasuring Customers’ Satisfaction Using Sentiment Analysis: Model and ToolAhmed Alqurafi, Tawfeeq AlsanoosyCustomer reviews are a valuable data resource for business owners and companies. Customers frequently write reviews on many platforms, such as eBay or Amazon. These reviews show, for instance, to what extent customers are satisfied with a service or a product. Therefore, these reviews can be used by companies and business owners to improve their services or products. However, numerous … …Journal of Computer Science, Vol. 20, Issue 4 · 7 Feb 2024 · 6,471 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzyNET: A Fuzzy Logic-Based Framework for Enhancing Urban Efficiency in Smart CitiesHemant Kumar, Safdar Tanweer, Parul Agarwal et al.The smart city paradigm emphasizes the strategic use of IoT, Big Data, and digital technologies to optimize urban operations and improve service delivery for citizens. Embedding digital technologies within operational workflows is driven by the objective of improving efficiency and long-term sustainability. The core transformation is Artificial Intelligence (AI) that revolutionizes management of cities through automation and instantaneous decisions based … …Journal of Computer Science, Vol. 22, Issue 7 · 19 Jul 2026 · 820 accessesView PDFCite