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73 results for “Bi-LSTM Model”
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Research ArticleOpen accessIn the abstractSuVashantor: English to Bangla Machine Translation SystemsMahjabeen Akter, M. Shahidur Rahman, Muhammed Zafar Iqbal, Mohammad Reza SelimThis paper presents the system description of Machine Translation (MT) systems for English-Bangla language pair. Our goal was to create two benchmark MT systems that produce a better quality translation and comparatively higher evaluation score than existing MT systems for English to Bangla. In our experiments, we implemented two baseline MT systems using both statistical and neural methods for the … …Journal of Computer Science, Vol. 16, Issue 8 · 16 Aug 2020 · 7,445 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Air Passenger Demand: A Comparison of LSTM and SARIMAQuang Hung Do, Shih-Kuei Lo, Jeng-Fung Chen et al.All airports need to have an accurate prediction of the number of passengers for their efficient management. An accurate prediction of the number of air passengers is crucial task since it provides information for planning decisions in the airport infrastructure to stabilize the service and maximize the profit. This study proposes a novel air passenger demand forecasting model based on … …Journal of Computer Science, Vol. 16, Issue 7 · 25 Jul 2020 · 8,555 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Evaluation of Deep Learning Networks on Printed Odia CharactersSanjibani Sudha Pattanayak, Sateesh Kumar Pradhan, Ramesh Chandra MalikDeep machine learning includes a series of layers to mimic the working of the human brain for taking a decision. Deep learning networks have shown good results in character recognition in the past. This paper evaluates the performance of different deep learning networks like Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM) based recurrent neural network and Convolutional LSTM on … …Journal of Computer Science, Vol. 16, Issue 7 · 25 Jul 2020 · 6,785 accessesView PDFCite
Research ArticleOpen accessIn the abstractEmail Spam Classification Using Gated Recurrent Unit and Long Short-Term MemoryIqbal Basyar, Adiwijaya, Danang Triantoro MurdiansyahHigh numbers of spam emails have led to an increase in email triage, causing losses amounting to USD 355 million per year. One way to reduce this loss is to classify spam email into categories including fraud or promotions made by unwanted parties. The initial development of spam email classification was based on simple methods such as word filters. Now, … …Journal of Computer Science, Vol. 16, Issue 4 · 3 Apr 2020 · 8,323 accessesView PDFCite
Research ArticleOpen accessIn the abstractLong Short-Term Memory Model for Classification of English-PtBR Cross-Lingual Hate SpeechThiago D. Bispo, Hendrik T. Macedo, Flávio de O. Santos et al.Automatic and accurate recognition of hate speech is a difficult job. In addition to the inherent ambiguity of the natural language, deep understanding of the linguistic structure is imperative. Usually, discriminatory discourse does not make use of typical expressions and often abuse of sarcasm. Good knowledge of world and assessment of context are thus highly demanded. Several approaches have been … …Journal of Computer Science, Vol. 15, Issue 10 · 1 Nov 2019 · 7,338 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning and Deep Learning for Phishing Email Classification using One-Hot EncodingSikha Bagui, Debarghya Nandi, Subhash Bagui, Robert Jamie WhiteRepresentation of text is a significant task in Natural Language Processing (NLP) and in recent years Deep Learning (DL) and Machine Learning (ML) have been widely used in various NLP tasks like topic classification, sentiment analysis and language translation. Until very recently, little work has been devoted to semantic analysis in phishing detection or phishing email detection. The novelty of … …Journal of Computer Science, Vol. 17, Issue 7 · 23 Jul 2021 · 10,936 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAdvanced Hierarchical Deep Learning Approach for Intrusion Detection: Hyperparameter Tuning and Performance Evaluation on the CICIDS DatasetAjeet Singh, Azath M, Shahazad Niwazi Qurashi et al.Intrusion Detection Systems (IDS) are essential in the communication security and integrity of contemporary network architectures. This study introduces a novel advanced hierarchical deep learning model for network intrusion detection using the CICIDS dataset-2019. To improve the detection accuracy, the proposed model architecture builds several deep learning layers embedded with hyperparameters' optimization. Additional preprocessing steps, including over-sampling and min-max scaling, … …Journal of Computer Science, Vol. 21, Issue 11 · 26 Dec 2025 · 2,148 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDecoding Discrepancies: Understanding Rating and Review Gaps in Best-Selling ProductsJyoti S Verma, Jaimin N UndaviaClassification of the sentiment and using it for the rating prediction is the major task don in this paper. The emotions and opinions are expressed by the users about a product on the e-commerce website and this provides the basis for the prediction done here. The prediction of the rating enables both the user as well as the seller as … …Journal of Computer Science, Vol. 21, Issue 6 · 29 May 2025 · 5,025 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordComparative Study of Garuda Indonesia Stock Price Prediction Using SVM, LSTM and Multiple Linear RegressionMuhammad Naufal Luthfi, Evaristus Didik MadyatmadjaStock shares are one of the investment products or tools that have been used by many people. Shares have interesting options for saving or investment and are able to provide attractive returns based on corporate or company growth. Many factors can affect the share prices, whether internal or external companies. This research was conducted on Garuda Indonesia's stock price with … …Journal of Computer Science, Vol. 21, Issue 4 · 25 Mar 2025 · 5,032 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAspect Category Detection Using Bi-LSTM-Based Deep Learning for Sentiment Analysis for HindiAshwani Gupta, Utpal SharmaIn the field of sentiment analysis, the notion of aspect category identification lays emphasis on identifying the aspect categories in a specific review phrase. The purpose of this research is to propose a novel approach to the identification of aspect categories in reviews that are published in Hindi. The training and evaluation of a supervised model that is based on … …Journal of Computer Science, Vol. 20, Issue 11 · 18 Sep 2024 · 4,606 accessesView PDFCite