Deep learning and linguistic representation. (2021)

• Record Type: Book
• Further Information: Note: Shalom Lappin.
• Authors: Lappin, Shalom
• Contents: Chapter 1 Introduction: Deep Learning in Natural Language Processing ; 1.1 OUTLINE OF THE BOOK ; 1.2 FROM ENGINEERING TO COGNITIVE SCIENCE ; 1.3 ELEMENTS OF DEEP LEARNING ; 1.4 TYPES OF DEEP NEURAL NETWORKS ; 1.5 AN EXAMPLE APPLICATION ; 1.6 SUMMARY AND CONCLUSIONS Chapter 2 Learning Syntactic Structure with Deep Neural Networks ; 2.1 SUBJECT-VERB AGREEMENT ; 2.2 ARCHITECTURE AND EXPERIMENTS ; 2.3 HIERARCHICAL STRUCTURE ; 2.4 TREE DNNS ; 2.5 SUMMARY AND CONCLUSIONS Chapter 3 Machine Learning and The Sentence Acceptability Task ; 3.1 GRADIENCE IN SENTENCE ACCEPTABILITY ; 3.2 PREDICTING ACCEPTABILITY WITH MACHINE LEARNING MODELS ; 3.3 ADDING TAGS AND TREES ; 3.4 SUMMARY AND CONCLUSIONS Chapter 4 Predicting Human Acceptability Judgments in Context; 4.1 ACCEPTABILITY JUDGMENTS IN CONTEXT ; 4.2 TWO SETS OF EXPERIMENTS ; 4.3 THE COMPRESSION EFFECT AND DISCOURSE COHERENCE; 4.4 PREDICTING ACCEPTABILITY WITH DIFFERENT DNN MODELS ; 4.5 SUMMARY AND CONCLUSIONS Chapter 5 Cognitively Viable Computational Models of Linguistic Knowledge ; 5.1 HOW USEFUL ARE LINGUISTIC THEORIES FOR NLP APPLICATIONS? ; 5.2 MACHINE LEARNING MODELS VS FORMAL GRAMMAR; 5.3 EXPLAINING LANGUAGE ACQUISITION ; 5.4 DEEP LEARNING AND DISTRIBUTIONAL SEMANTICS 1; 5.5 SUMMARY AND CONCLUSIONS Chapter 6 Conclusions and Future Work ; 6.1 REPRESENTING SYNTACTIC AND SEMANTIC KNOWLEDGE; 6.2 DOMAIN SPECIFIC LEARNING BIASES AND LANGUAGE ACQUISITION ; 6.3 DIRECTIONS FOR FUTURE WORK ; REFERENCES Author Index Subject Index
• Edition: 1st
• Publisher Details: Boca Raton : Chapman & Hall/CRC
• Publication Date: 2021
• Extent: 1 online resource, illustrations (black and white)
• Subjects: 410.285; Computational linguistics; Natural language processing (Computer science); Machine learning
• Languages: English
• ISBNs: 9781000380330; 9781000380323; 9781003127086
• Related ISBNs: 9780367649470; 9780367648749
• Notes: Note: Description based on CIP data; resource not viewed.
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