Da: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9786209879531
Quantità: Più di 20 disponibili
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
PAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L0-9786209879531
Quantità: Più di 20 disponibili
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 116 pp. Englisch. Codice articolo 9786209879531
Quantità: 2 disponibili
Da: CitiRetail, Stevenage, Regno Unito
Paperback. Condizione: new. Paperback. In the modern digital era, human communication has shifted significantly toward unstructured text found on social media, micro-blogs, and instant messaging platforms. While traditional face-to-face interactions rely on non-verbal cues like facial expressions and vocal tone, digital text lacks these signals, making the detection of emotional intent a complex challenge for Natural Language Processing (NLP). This study addresses the limitations of traditional machine learning methods, such as Naive Bayes and Logistic Regression, which often fail to capture contextual meaning and long-range sequential dependencies. The proposed research introduces a hybrid deep learning framework that integrates Word2Vec(Continuous Bag-of-Words) embeddings with a Bidirectional Long Short-Term Memory (BiLSTM) network. Word2Vec is utilized to extract dense semantic features, enabling the model to understand mathematical relationships between words. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9786209879531
Quantità: 1 disponibili
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 116 pp. Englisch. Codice articolo 9786209879531
Quantità: 1 disponibili
Da: preigu, Osnabrück, Germania
Taschenbuch. Condizione: Neu. Contextual Emotion Classification in Text Using Hybrid Word2Vec-BiLSTM | Deep Learning Approach | Nilla Sivasrinu (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786209879531 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Codice articolo 135358943
Quantità: 5 disponibili
Da: AHA-BUCH GmbH, Einbeck, Germania
Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering. Codice articolo 9786209879531
Quantità: 1 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26406615592
Quantità: 4 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand. Codice articolo 407620087
Quantità: 4 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND. Codice articolo 18406615586
Quantità: 4 disponibili