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Format: 1 online resource (366 pages)

ISBN: 9782494069374

Series Statement: Advances in Social Science, Education and Humanities Research Ser. ; v.691

Note: Intro -- Preface -- Organization -- Keynote Speeches -- The Effects of Social Media: Cultural Capital and Students' Social Media Usage -- Housing as a Nexus of Unaffordability, Illegality and Un-liveability: The Case of Hong Kong -- Evaluation of Mandarin Language Course at University of Technology MARA in Malaysia -- Adaptive Business Model and Its Application on Career Planning and Development -- Contents -- Peer-Review Statements -- 1 Review Procedure -- 2 Quality Criteria -- 3 Key Metrics -- 4 Competing Interests -- Education and Cultural Studies -- Analysis of Teaching Effectiveness in Several Teaching Modes -- 1 Several Abnormal Teaching Modes and Their Teaching Performance -- 1.1 "Reporting-Style" Teaching and "Narrating-Style" Teaching -- 1.2 "Copying-Style" Teaching -- 1.3 "Running-Style" Teaching -- 1.4 "Jam-Style" Teaching -- 2 Analysis and Thinking of Teaching Effectiveness -- 2.1 "Reporting-Style" and "Narrating-Style" Are Totally Unreliable -- 2.2 "Copying-Style" at Least Deviates from the Principle of Teaching Diversity -- 2.3 "Running-Style" Deviates from Three Principles -- 2.4 Serious "Teaching Jam" Does not Account for Five Principles -- 3 Conclusion -- References -- Self-media Literacy in Language Education and Cross Cultural Competence Development -- 1 Introduction -- 2 The Course and Theoretical Base -- 3 Integration and Experience -- 4 Conclusion -- 5 Suggestions for Future Studies -- References -- Innovative Development of Mathematics Beauty and Aesthetic Education -- 1 Introduction -- 2 Similarities and Differences Between Mathematical Beauty and Other Beauty -- 2.1 Process and Method of Comparative Study -- 2.2 Five Fields of Aesthetics in Mathematics and Other Disciplines -- 2.3 Research Conclusion -- 3 Conclusion -- References -- The Image of Supernatural Beings in Kongtong Wushu -- 1 Introduction. , 2 The Mythology of Kongtong Wushu -- 2.1 Nüwa and Kongtong Wushu -- 2.2 Fuxi and Kongtong Wushu -- 2.3 Yellow Emperor and Kongtong Wushu -- 2.4 Houji and Kongtong Wushu -- 3 Conclusion -- References -- A Study on the Word "Sleeve" in Japanese Waka -- 1 Introduction -- 2 High-Frequency Nouns in the Waka of the Tale of Genji -- 3 ''Sleeve'' in the Waka of the Tale of Genji -- 3.1 The Frequency and Distribution of "Sleeve" -- 3.2 Classification of the Noun ''Sleeve'' in the Waka of the Tale of Genji -- 4 Conclusion -- References -- Study on Model Course of Ideological and Political Demonstration Courses: Taking Modern Agricultural Innovation and Rural Revitalization Strategy as an Example -- 1 Introduction -- 2 Teach a Good Ideological and Political Course -- 2.1 Guide Students to Listen to the Party and Follow the Party -- 2.2 Guide Students to Establish Feelings for the People -- 2.3 Guide Students to Strengthen Institutional Self-confidence -- 2.4 Guide Students to Bravely Shoulder the Heavy Responsibilities of the Times -- 3 The Basic Ideas of Modern Agricultural Innovation and Rural Revitalization Strategy Course Ideological and Political Construction -- 4 Improve the Effectiveness of Ideological and Political Education in the Curriculum from Multiple Angles -- 4.1 Teach Students in Accordance with Their Aptitude -- 4.2 Emphasis on Teach Tactics -- 4.3 Continuous Summary Research -- 5 Ideological and Political Education is Imperceptibly Embedded in the Interaction Between Teaching and Learning -- 5.1 Students Are Trained to Think Independently -- 5.2 Combine Teaching with Stimulating Interest in Research -- 5.3 Focus on the Resonance of Teaching and Learning -- 6 Conclusion -- References -- Exploration of Innovative Teaching of ''Computer System Architecture'' -- 1 Introduction -- 2 Transformation of Experimental Teaching Concept. , 3 Open Labs in Conjunction with Research -- 4 Reform the Assessment of Experimental Performance -- 5 Conclusion -- References -- Corpus-Based Lexical Development of EFL Writing -- 1 Introduction -- 2 Method -- 2.1 Corpora -- 2.2 Data Collection and Data Analysis -- 3 Results -- 3.1 Types, Tokens and TTR -- 3.2 Unit Length -- 3.3 COCA Frequency List Coverage -- 3.4 Lexical Sophistication -- 3.5 Bigram and Trigram Complexity -- 4 Discussion and Conclusion -- References -- A Design of Translation Competence Evaluation Based on Analytic Hierarchy Process -- 1 Introduction -- 2 Determining the Core Evaluation Parameters -- 3 Designing the Translation Competence Evaluation Model -- 4 Calculating the Weights of the Core Parameters and Sub-indicators -- 5 Discussion -- 6 Conclusion -- References -- A Study of Facilitating the Enabling of the Lexical Chunk Output in the POA -- 1 Introduction -- 2 Route to the Enabling of the Lexical Chunks Output -- 2.1 Output Enabling of Lexical Chunk Based on Alignment -- 2.2 Output Enabling of Lexical Chunk Based on Gradualness -- 2.3 Output Enabling of Lexical Chunk Based on Variety -- 3 Conclusion -- References -- Exploration and Practice of Ideological and Political Teaching Mode of Environmental Fluid Mechanics Under the International Talent Training Mode -- 1 Significance of the Study -- 2 Existing Problems -- 2.1 Single Form of Ideological and Political Teaching -- 2.2 Decoupling of Ideological and Political Elements from Curriculum Content -- 2.3 Difficult to Achieve the Goal of International Training -- 3 Reform and Innovation -- 3.1 Mining Ideological and Political Elements -- 3.2 Reform Teaching Methods -- 4 Conclusions -- References -- An Educative Approach to Booth Assignment for a School Carnival -- 1 Introduction -- 2 The Problem -- 3 The Proposed Appraoch -- 4 Results and Discussion -- 5 Concluding Remarks. , References -- Teaching Reform and Practice Based on OBE Concept -- 1 Introduction -- 2 Curriculum Training Objectives -- 3 Design of Task-Driven Teaching Implementation Plan Based on OBE Concept -- 3.1 Teaching Model and Methodology Design Based on OBE -- 3.2 Student-Led Teaching -- 4 Evaluation of Teaching Effectiveness -- 5 Conclusions -- References -- Induction and Reflection in Linear Algebra Teaching -- 1 Induction and Summary of the Scattered Knowledge -- 1.1 The Operational Properties of the Matrix [1] -- 1.2 Equivalent Scale of the Matrix Rank [2] -- 1.3 The Induction of the Invertible Matrix [3] -- 1.4 Application of the Elementary Transformation [4] -- 2 Refining Summary of the Knowledge -- 2.1 Identification Theorem for the Linear Correlations of Vector Groups [5] -- 2.2 The Properties of the Determinant [5] -- 2.3 The Properties of Inverse Matrices [5] -- 2.4 The Relationship Between the Solution of Linear Equations and the Linear Dependence of Vectors -- 3 Generalization From Special to General [6] -- 4 The Comparison and Induction of Different Knowledge Points -- 4.1 The Definition of Matrix Equivalence, Similarity and Congruence is Compared and Summarized -- 4.2 The Relation of Matrix Equivalence, Similarity, Congruence are Compared and Summarized (Fig. 1) -- 4.3 The Properties of Matrix Equivalence, Similarity and Congruence are Compared and Summarized (Table 2) -- 4.4 Equivalence Classes of Matrix Equivalence, Similarity and Congruence are Compared and Summarized -- 4.5 Refinement of the Main Line of Knowledge [3] -- 5 Conclusion -- References -- Zebrafish as a Model Animal to Strengthen the Discipline Understanding and Interest Guidance of Students Majoring in Green Chemical Engineering and Biomedicine -- 1 Introduction -- 2 Methods -- 3 Results and Discussion -- 4 Conclusions -- References. , An Analysis on the Current State of Doctoral Training in Physical Oceanography of Ocean University of China -- 1 Introduction -- 2 Data Source and Processing -- 2.1 Source of Doctoral Students List -- 2.2 Source of Doctoral Student's Published Papers -- 2.3 Source of Research Samples -- 3 Data Statistical Analysis Methods and Results -- 3.1 Study Sample Statistics -- 3.2 Statistical Analysis According to the Classification of the Number of Published Papers -- 3.3 Assessment of Paper Quality -- 4 Conclusions and Recommendations -- References -- Design and Implementation of Online First-Class Course "Innovative Thinking Methods" -- 1 Introduction -- 2 Basic Information of Course Construction -- 3 Innovate Educational Idea and Course Goal -- 3.1 Innovate Educational Idea -- 3.2 Course Goal -- 4 Innovative Design of Course Teaching -- 4.1 Systematic Analysis of Course Content -- 4.2 Innovative Design of Course Teaching -- 5 Curriculum Implementation and Application Promotion -- 6 Conclusion -- Bibliography -- The Exploration and Practice of Process Assessment of the Online Teaching: A Case Study on Specialty English for Environmental Science and Engineering -- 1 Introduction -- 2 Design and Implementation of Process Assessment -- 2.1 Assessment Time Resetting -- 2.2 The Change of the Evaluation Method -- 2.3 The Change of the Evaluation Purpose -- 3 Design and Implementation of Process Assessment -- 3.1 Assessment Time Resetting -- 3.2 Further Work for Process Assessment -- 4 Conclusions -- References -- Research on the Thematic Teaching of the Outline of Modern and Contemporary Chinese History Based on the BOPPPS Teaching Method -- 1 The Conformity of Thematic Teaching and BOPPPS Teaching Method -- 1.1 Both Seek to Transform the Textbook System into a Teaching System -- 1.2 Both Pursue Teaching Activities Around Teaching Objective. , 1.3 Both Pursue the Logic of the Teaching System.

Additional Edition: Print version: Yau, Yung Proceedings of the 2022 International Conference on Diversified Education and Social Development (DESD 2022) Paris : Atlantis Press (Zeger Karssen),c2023 ISBN 9782494069367

Language: English

Keywords: Electronic books. ; Congressos ; Llibres electrònics

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Format: 216 S.

Language: German

Subjects: German Studies

URL: http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=002291622&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA

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Author information: Frank, Bruno, 1887-1945.

UID:

Format: 1 online resource (VIII, 300 p.)

Edition: 1st ed. 1994.

Edition: Online edition Springer Lecture Notes Archive ; 041142-5

ISBN: 3-540-48985-1

Series Statement: Lecture Notes in Artificial Intelligence ; 862

Content: This volume presents the proceedings of the Second International Colloquium on Grammatical Inference (ICGI-94), held in Alicante, Spain in September 1994. Besides 25 research papers carefully selected and refereed by the program committee, the book contains a survey by E. Vidal. The book is devoted to all those aspects of automatic learning that explicitly focus on principles, theory, and applications of grammars and languages. The papers are organized in sections on formal aspects; language modelling and linguistic applications; stochastic approaches, applications and performance analysis; and neural networks, genetic algorithms, and artificial intelligence techniques.

Note: Bibliographic Level Mode of Issuance: Monograph , Grammatical inference: An introductory survey -- Learning morphology — practice makes good -- A hierarchy of language families learnable by regular language learners -- What is the search space of the regular inference? -- A characterization of even Linear Languages and its application to the learning problem -- Object-Oriented inferences in a logical framework for feature grammars -- Automatic determination of a stochastic bi-gram class language model -- The acquisition of a lexicon from paired phoneme sequences and semantic representations -- Inference and estimation of a long-range trigram model -- Application of OSTIA to machine translation tasks -- Inducing probabilistic grammars by Bayesian model merging -- Statistical estimation of Stochastic Context-Free Grammars using the Inside-Outside algorithm and a transformation on grammars -- Statistical inductive learning of regular formal languages -- Learning stochastic regular grammars by means of a state merging method -- Forming grammars for structured documents: an application of grammatical inference -- A comparison of syntactic and statistical techniques for off-line OCR -- The algorithms RT and k-TTI: A first comparison -- Dynamic grammatical representations in guided propagation networks -- A hybrid connectionist-symbolic approach to regular grammatical inference based on neural learning and hierarchical clustering -- Inference of context-free grammars by enumeration: Structural containment as an ordering bias -- Representational issues for context free grammar induction using genetic algorithms -- Regular grammatical inference from positive and negative samples by genetic search: the GIG method -- Training and application of integrated grammar/bigram language models -- Learning unification-based grammars using the Spoken English Corpus -- Stochastic optimization of a probabilistic language model -- Computer assisted grammar construction. , English

In: Springer eBooks

Additional Edition: ISBN 3-540-58473-0

Language: English

DOI: 10.1007/3-540-58473-0

URL: http://dx.doi.org/10.1007/3-540-58473-0

URL: http://dx.doi.org/10.1007/3-540-58473-0

UID:

Format: Online-Ressource (VIII, 290 S.)

Edition: Online-Ausg. Berlin [u.a.] Springer 2006 Springer lecture notes archive

ISBN: 9783540489856

Series Statement: Lecture notes in computer science 862

Content: Grammatical inference: An introductory survey -- Learning morphology — practice makes good -- A hierarchy of language families learnable by regular language learners -- What is the search space of the regular inference? -- A characterization of even Linear Languages and its application to the learning problem -- Object-Oriented inferences in a logical framework for feature grammars -- Automatic determination of a stochastic bi-gram class language model -- The acquisition of a lexicon from paired phoneme sequences and semantic representations -- Inference and estimation of a long-range trigram model -- Application of OSTIA to machine translation tasks -- Inducing probabilistic grammars by Bayesian model merging -- Statistical estimation of Stochastic Context-Free Grammars using the Inside-Outside algorithm and a transformation on grammars -- Statistical inductive learning of regular formal languages -- Learning stochastic regular grammars by means of a state merging method -- Forming grammars for structured documents: an application of grammatical inference -- A comparison of syntactic and statistical techniques for off-line OCR -- The algorithms RT and k-TTI: A first comparison -- Dynamic grammatical representations in guided propagation networks -- A hybrid connectionist-symbolic approach to regular grammatical inference based on neural learning and hierarchical clustering -- Inference of context-free grammars by enumeration: Structural containment as an ordering bias -- Representational issues for context free grammar induction using genetic algorithms -- Regular grammatical inference from positive and negative samples by genetic search: the GIG method -- Training and application of integrated grammar/bigram language models -- Learning unification-based grammars using the Spoken English Corpus -- Stochastic optimization of a probabilistic language model -- Computer assisted grammar construction.

Content: This volume presents the proceedings of the Second International Colloquium on Grammatical Inference (ICGI-94), held in Alicante, Spain in September 1994. Besides 25 research papers carefully selected and refereed by the program committee, the book contains a survey by E. Vidal. The book is devoted to all those aspects of automatic learning that explicitly focus on principles, theory, and applications of grammars and languages. The papers are organized in sections on formal aspects; language modelling and linguistic applications; stochastic approaches, applications and performance analysis; and neural networks, genetic algorithms, and artificial intelligence techniques.

Note: Literaturangaben

Additional Edition: ISBN 3540584730

Additional Edition: ISBN 9783540584735

Additional Edition: Erscheint auch als Druck-Ausgabe Grammatical inference and applications Berlin : Springer, 1994 ISBN 3540584730

Additional Edition: ISBN 0387584730

Language: English

Subjects: Computer Science

Keywords: Grammatiktheorie ; Konferenzschrift

DOI: 10.1007/3-540-58473-0

URL: Volltext  (lizenzpflichtig)

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Format: 1 online resource (264 p.)

ISBN: 9781788924863

Series Statement: Second Language Acquisition ; 148

Content: This is the first book to investigate the field of phraseology from a learner corpus perspective. It includes cutting-edge studies which analyse a wide range of multiword units and extensive learner corpus data to provide the reader with a comprehensive theoretical, methodological and applied perspective onto L2 use in a wide range of situations.

Note: Frontmatter -- , Contents -- , Contributors -- , Part 1: Introduction -- , 1 Phraseology, Corpora and L2 Research -- , Part 2: The Learner Phrasicon: Synchronic Approaches -- , 2 The Functions of N-grams in Bilingual and Learner Corpora: An Integrated Contrastive Approach -- , 3 Exploring Learner Corpus Data for Language Testing and Assessment Purposes: The Case of Verb + Noun Collocations -- , 4 The Passive and the Lexis-Grammar Interface: An Inter-varietal Perspective -- , Part 3: The Learner Phrasicon: Developmental Approaches -- , 5 Phraseological Complexity as an Index of L2 Dutch Writing Proficiency: A Partial Replication Study -- , 6 Automatically Assessing Lexical Sophistication Using Word, Bigram, and Dependency Indices -- , 7 Adjective + Noun Collocations in L2 and L1 Speech: Evidence from the Trinity Lancaster Corpus and the Spoken BNC2014 -- , 8 Development of Formulaic Knowledge in Learner Writing: A Longitudinal Perspective -- , 9 Tracing Collocation in Learner Production and Processing: Integrating Corpus Linguistic and Experimental Approaches -- , Part 4: Postface -- , 10 Phrasicon, Phrase, Phraseology -- , Index , In English.

Language: English

Subjects: Comparative Studies. Non-European Languages/Literatures

DOI: 10.21832/9781788924863

URL: https://doi.org/10.21832/9781788924863

URL: https://www.degruyter.com/isbn/9781788924863

URL: https://doi.org/10.21832/9781788924863

URL: https://www.degruyter.com/isbn/9781788924863

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Format: 1 online resource (292 pages) : , illustrations

Edition: 1st edition

Content: Leverage the power of Python to collect, process, and mine deep insights from social media data About This Book Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more Analyze and extract actionable insights from your social data using various Python tools A highly practical guide to conducting efficient social media analytics at scale Who This Book Is For If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process. What You Will Learn Understand the basics of social media mining Use PyMongo to clean, store, and access data in MongoDB Understand user reactions and emotion detection on Facebook Perform Twitter sentiment analysis and entity recognition using Python Analyze video and campaign performance on YouTube Mine popular trends on GitHub and predict the next big technology Extract conversational topics on public internet forums Analyze user interests on Pinterest Perform large-scale social media analytics on the cloud In Detail Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business. Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes. Style and approach This book follows a step-by-step approach to teach readers the concepts of social media analytics using th...

Note: Includes index. , Cover -- Copyright -- Credits -- About the Authors -- Acknowledgments -- About the Reviewer -- www.PacktPub.com -- Customer Feedback -- Table of Contents -- Preface -- Chapter 1: Introduction to the Latest Social Media Landscape and Importance -- Introducing social graph -- Notion of influence -- Social impacts -- Platforms on platform -- Delving into social data -- Understanding semantics -- Defining the semantic web -- Exploring social data applications -- Understanding the process -- Working environment -- Defining Python -- Selecting an IDE -- Illustrating Git -- Getting the data -- Defining API -- Scraping and crawling -- Analyzing the data -- Brief introduction to machine learning -- Techniques for social media analysis -- Setting up data structure libraries -- Visualizing the data -- Getting started with the toolset -- Summary -- Chapter 2: Harnessing Social Data - Connecting, Capturing, and Cleaning -- APIs in a nutshell -- Different types of API -- RESTful API -- Stream API -- Advantages of social media APIs -- Limitations of social media APIs -- Connecting principles of APIs -- Introduction to authentication techniques -- What is OAuth? -- User authentication -- Application authentication -- Why do we need to use OAuth? -- Connecting to social network platforms without OAuth -- OAuth1 and OAuth2 -- Practical usage of OAuth -- Parsing API outputs -- Twitter -- Creating application -- Selecting the endpoint -- Using requests to connect -- Facebook -- Creating an app and getting an access token -- Selecting the endpoint -- Connect to the API -- GitHub -- Obtaining OAuth tokens programmatically -- Selecting the endpoint -- Connecting to the API -- YouTube -- Creating an application and obtaining an access token programmatically -- Selecting the endpoint -- Connecting to the API -- Pinterest -- Creating an application. , Selecting the endpoint -- Connecting to the API -- Basic cleaning techniques -- Data type and encoding -- Structure of data -- Pre-processing and text normalization -- Duplicate removal -- MongoDB to store and access social data -- Installing MongoDB -- Setting up the environment -- Starting MongoDB -- MongoDB using Python -- Summary -- Chapter 3: Uncovering Brand Activity, Popularity, and Emotions on Facebook -- Facebook brand page -- The Facebook API -- Project planning -- Scope and process -- Data type -- Analysis -- Step 1 - data extraction -- Step 2 - data pull -- Step 3 - feature extraction -- Step 4 - content analysis -- Keywords -- Extracting verbatims for keywords -- User keywords -- Brand posts -- User hashtags -- Noun phrases -- Brand posts -- User comments -- Detecting trends in time series -- Maximum shares -- Brand posts -- User comments -- Maximum likes -- Brand posts -- Comments -- Uncovering emotions -- How to extract emotions? -- Introducing the Alchemy API -- Connecting to the Alchemy API -- Setting up an application -- Applying Alchemy API -- How can brands benefit from it? -- Summary -- Chapter 4: Analyzing Twitter Using Sentiment Analysis and Entity Recognition -- Scope and process -- Getting the data -- Getting Twitter API keys -- Data extraction -- REST API Search endpoint -- Rate Limits -- Streaming API -- Data pull -- Data cleaning -- Sentiment analysis -- Customized sentiment analysis -- Labeling the data -- Creating the model -- Model performance evaluation and cross-validation -- Confusion matrix -- K-fold cross-validation -- Named entity recognition -- Installing NER -- Combining NER and sentiment analysis -- Summary -- Chapter 5: Campaigns and Consumer Reaction Analytics on YouTube - Structured and Unstructured -- Scope and process -- Getting the data -- How to get a YouTube API key -- Data pull -- Data processing. , Data analysis -- Sentiment analysis in time -- Sentiment by weekday -- Comments in time -- Number of comments by weekday -- Summary -- Chapter 6: The Next Great Technology - Trends Mining on GitHub -- Scope and process -- Getting the data -- Rate Limits -- Connection to GitHub -- Data pull -- Data processing -- Textual data -- Numerical data -- Data analysis -- Top technologies -- Programming languages -- Programming languages used in top technologies -- Top repositories by technology -- Comparison of technologies in terms of forks, open issues, size, and watchers count -- Forks versus open issues -- Forks versus size -- Forks versus watchers -- Open issues versus Size -- Open issues versus Watchers -- Size versus watchers -- Summary -- Chapter 7: Scraping and Extracting Conversational Topics on Internet Forums -- Scope and process -- Getting the data -- Introduction to scraping -- Scrapy framework -- How it works -- Related tools -- Creating a project -- Creating spiders -- Teamspeed forum spider -- Data pull and pre-processing -- Data cleaning -- Part-of-speech extraction -- Data analysis -- Introduction to topic models -- Latent Dirichlet Allocation -- Applying LDA to forum conversations -- Topic interpretation -- Summary -- Chapter 8: Demystifying Pinterest through Network Analysis of Users Interests -- Scope and process -- Getting the data -- Pinterest API -- Step 1 - creating an application and obtaining app ID and app secret -- Step 2 - getting your authorization code (access code) -- Step 3 - exchanging the access code for an access token -- Step 4 - testing the connection -- Getting Pinterest API data -- Scraping Pinterest search results -- Building a scraper with Selenium -- Scraping time constraints -- Data pull and pre-processing -- Pinterest API data -- Bigram extraction -- Building a graph -- Pinterest search results data. , Bigram extraction -- Building a graph -- Data analysis -- Understanding relationships between our own topics -- Finding influencers -- Conclusions -- Community structure -- Summary -- Chapter 9: Social Data Analytics at Scale - Spark and Amazon Web Services -- Different scaling methods and platforms -- Parallel computing -- Distributed computing with Celery -- Celery multiple node deployment -- Distributed computing with Spark -- Text mining With Spark -- Topic models at scale -- Spark on the Cloud - Amazon Elastic MapReduce -- Summary -- Index.

Additional Edition: ISBN 1-78712-148-8

Additional Edition: ISBN 1-78712-675-7

Language: English

UID:

Format: 1 Online-Ressource

ISBN: 9781799811619

Content: "This book examines natural language processing models and algorithms using traditional symbolic and more recent statistical approaches"--

Note: Chapter 1. Deep learning network: deep neural networks -- Chapter 2. A journey from neural networks to deep networks: comprehensive understanding for deep learning -- Chapter 3. Current trends in deep learning frameworks with opportunities and future prospectus -- Chapter 4. Emotion recognition from speech using perceptual filter and neural network -- Chapter 5. Ontology creation -- Chapter 6. Semantic similarity using register linear question classification (RLQC) for question classification -- Chapter 7. Knowledge graph generation -- Chapter 8. Develop a neural model to score bigram of words using bag-of-words model for sentiment analysis -- Chapter 9. Deep learning approach for extracting catch phrases from legal documents -- Chapter 10. Enhanced sentiment classification using recurrent neural networks -- Chapter 11. Natural language processing-based information extraction and abstraction for lease documents -- Chapter 12. Neural network applications in hate speech detection

Additional Edition: Erscheint auch als Druck-Ausgabe, hardcover ISBN 978-1-7998-1159-6

Additional Edition: Erscheint auch als Druck-Ausgabe, softcover ISBN 978-1-7998-1160-2

Language: English

URL: Volltext  (URL des Erstveröffentlichers)

UID:

Format: XX, 723 p. 307 illus., 249 illus. in color. , online resource.

Edition: 1st ed. 2021.

ISBN: 9789813346734

Series Statement: Advances in Intelligent Systems and Computing, 1309

Content: This book presents various computational and cognitive modeling approaches in the areas of health, education, finance, environment, engineering, commerce, and industry. It is a collection of selected conference papers presented at the International Conference on Trends in Computational and Cognitive Engineering (TCCE 2020). It shares cutting-edge insights and ideas from mathematicians, engineers, scientists, and researchers and discusses fresh perspectives on problem solving in a range of research areas.

Note: Chapter 1. Bangla Real-Word Error Detection and Correction Using Bidirectional LSTM and Bigram Hybrid Model -- Chapter 2. Quantitative Analysis of Deep CNNs for Multilingual Handwritten Digit Recognition -- Chapter 3. Performance Analysis of Machine Learning Approaches in Software Complexity Prediction -- Chapter 4. Bengali Abstractive News Summarization (BANS): A Neural Attention Approach -- Chapter 5. Application of Feature Engineering with Classification Techniques to Enhance Corporate Tax Default Detection Performance -- Chapter 6. PRCMLA: Product Review Classification using Machine Learning Algorithms -- Chapter 7. Handwritten Bangla Character Recognition Using Deep Convolutional Neural Network: Comprehensive Analysis on Three Complete Datasets -- Chapter 8. Handwritten Bangla Character Recognition Using Convolutional Neural Network and Bidirectional Long Short-Term Memory -- Chapter 9. Bangla Text Generation Using Bidirectional Optimized Gated Recurrent Unit Network -- Chapter 10. An ANN-based Approach to Identify Smart Appliances for Ambient Assisted Living (AAL) in the Smart Space.

In: Springer Nature eBook

Additional Edition: Printed edition: ISBN 9789813346727

Additional Edition: Printed edition: ISBN 9789813346741

Language: English

DOI: 10.1007/978-981-33-4673-4

URL: https://doi.org/10.1007/978-981-33-4673-4

UID:

Format: 1 online resource (XX, 723 p. 307 illus., 249 illus. in color.)

Edition: 1st ed. 2021.

ISBN: 981-334-673-6

Series Statement: Advances in Intelligent Systems and Computing, 1309

Content: This book presents various computational and cognitive modeling approaches in the areas of health, education, finance, environment, engineering, commerce, and industry. It is a collection of selected conference papers presented at the International Conference on Trends in Computational and Cognitive Engineering (TCCE 2020). It shares cutting-edge insights and ideas from mathematicians, engineers, scientists, and researchers and discusses fresh perspectives on problem solving in a range of research areas.

Note: Includes index. , Chapter 1. Bangla Real-Word Error Detection and Correction Using Bidirectional LSTM and Bigram Hybrid Model -- Chapter 2. Quantitative Analysis of Deep CNNs for Multilingual Handwritten Digit Recognition -- Chapter 3. Performance Analysis of Machine Learning Approaches in Software Complexity Prediction -- Chapter 4. Bengali Abstractive News Summarization (BANS): A Neural Attention Approach -- Chapter 5. Application of Feature Engineering with Classification Techniques to Enhance Corporate Tax Default Detection Performance -- Chapter 6. PRCMLA: Product Review Classification using Machine Learning Algorithms -- Chapter 7. Handwritten Bangla Character Recognition Using Deep Convolutional Neural Network: Comprehensive Analysis on Three Complete Datasets -- Chapter 8. Handwritten Bangla Character Recognition Using Convolutional Neural Network and Bidirectional Long Short-Term Memory -- Chapter 9. Bangla Text Generation Using Bidirectional Optimized Gated Recurrent Unit Network -- Chapter 10. An ANN-based Approach to Identify Smart Appliances for Ambient Assisted Living (AAL) in the Smart Space.

Additional Edition: ISBN 981-334-672-8

Language: English

DOI: 10.1007/978-981-33-4673-4

UID:

Format: VIII, 300 p. , online resource.

ISBN: 9783540489856

Series Statement: Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence, 862

Content: This volume presents the proceedings of the Second International Colloquium on Grammatical Inference (ICGI-94), held in Alicante, Spain in September 1994. Besides 25 research papers carefully selected and refereed by the program committee, the book contains a survey by E. Vidal. The book is devoted to all those aspects of automatic learning that explicitly focus on principles, theory, and applications of grammars and languages. The papers are organized in sections on formal aspects; language modelling and linguistic applications; stochastic approaches, applications and performance analysis; and neural networks, genetic algorithms, and artificial intelligence techniques.

Note: Grammatical inference: An introductory survey -- Learning morphology — practice makes good -- A hierarchy of language families learnable by regular language learners -- What is the search space of the regular inference? -- A characterization of even Linear Languages and its application to the learning problem -- Object-Oriented inferences in a logical framework for feature grammars -- Automatic determination of a stochastic bi-gram class language model -- The acquisition of a lexicon from paired phoneme sequences and semantic representations -- Inference and estimation of a long-range trigram model -- Application of OSTIA to machine translation tasks -- Inducing probabilistic grammars by Bayesian model merging -- Statistical estimation of Stochastic Context-Free Grammars using the Inside-Outside algorithm and a transformation on grammars -- Statistical inductive learning of regular formal languages -- Learning stochastic regular grammars by means of a state merging method -- Forming grammars for structured documents: an application of grammatical inference -- A comparison of syntactic and statistical techniques for off-line OCR -- The algorithms RT and k-TTI: A first comparison -- Dynamic grammatical representations in guided propagation networks -- A hybrid connectionist-symbolic approach to regular grammatical inference based on neural learning and hierarchical clustering -- Inference of context-free grammars by enumeration: Structural containment as an ordering bias -- Representational issues for context free grammar induction using genetic algorithms -- Regular grammatical inference from positive and negative samples by genetic search: the GIG method -- Training and application of integrated grammar/bigram language models -- Learning unification-based grammars using the Spoken English Corpus -- Stochastic optimization of a probabilistic language model -- Computer assisted grammar construction.

In: Springer eBooks

Additional Edition: Printed edition: ISBN 9783540584735

Language: English

DOI: 10.1007/3-540-58473-0

URL: http://dx.doi.org/10.1007/3-540-58473-0