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Data Science in Societal Applications [[electronic resource] ] : Concepts and Implications / / edited by Siddharth Swarup Rautaray, Manjusha Pandey, Nhu Gia Nguyen
| Data Science in Societal Applications [[electronic resource] ] : Concepts and Implications / / edited by Siddharth Swarup Rautaray, Manjusha Pandey, Nhu Gia Nguyen |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (199 pages) |
| Disciplina | 005.7 |
| Collana | Studies in Big Data |
| Soggetto topico |
Artificial intelligence - Data processing
Application software Big data Quantitative research Data Science Computer and Information Systems Applications Big Data Data Analysis and Big Data |
| ISBN | 981-19-5154-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cloud GIS Model for Coastal Geospatial Big Data Analytics -- Appealing AI in Appalling Covid-19 Crisis and the Impending -- Role of Data Science in Programmatic Advertising -- Social Development Data and Societal Modelling: A study in Indian Context -- Deep learning Trends and Inspired Systems in Natural Language Processing. |
| Record Nr. | UNINA-9910739441303321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Data Science in Societal Applications [[electronic resource] ] : Concepts and Implications / / edited by Siddharth Swarup Rautaray, Manjusha Pandey, Nhu Gia Nguyen
| Data Science in Societal Applications [[electronic resource] ] : Concepts and Implications / / edited by Siddharth Swarup Rautaray, Manjusha Pandey, Nhu Gia Nguyen |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (199 pages) |
| Disciplina | 005.7 |
| Collana | Studies in Big Data |
| Soggetto topico |
Artificial intelligence - Data processing
Application software Big data Quantitative research Data Science Computer and Information Systems Applications Big Data Data Analysis and Big Data |
| ISBN | 981-19-5154-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Cloud GIS Model for Coastal Geospatial Big Data Analytics -- Appealing AI in Appalling Covid-19 Crisis and the Impending -- Role of Data Science in Programmatic Advertising -- Social Development Data and Societal Modelling: A study in Indian Context -- Deep learning Trends and Inspired Systems in Natural Language Processing. |
| Record Nr. | UNISA-996490362603316 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Innovations for Community Services [[electronic resource] ] : 20th International Conference, I4CS 2020, Bhubaneswar, India, January 12–14, 2020, Proceedings / / edited by Siddharth Swarup Rautaray, Gerald Eichler, Christian Erfurth, Günter Fahrnberger
| Innovations for Community Services [[electronic resource] ] : 20th International Conference, I4CS 2020, Bhubaneswar, India, January 12–14, 2020, Proceedings / / edited by Siddharth Swarup Rautaray, Gerald Eichler, Christian Erfurth, Günter Fahrnberger |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xiii, 325 pages) : illustrations |
| Disciplina | 004.36 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer communication systems
Computers Architecture, Computer Special purpose computers Coding theory Information theory Software engineering Computer Communication Networks Information Systems and Communication Service Computer System Implementation Special Purpose and Application-Based Systems Coding and Information Theory Software Engineering |
| ISBN | 3-030-37484-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910366658003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Innovations for Community Services [[electronic resource] ] : 20th International Conference, I4CS 2020, Bhubaneswar, India, January 12–14, 2020, Proceedings / / edited by Siddharth Swarup Rautaray, Gerald Eichler, Christian Erfurth, Günter Fahrnberger
| Innovations for Community Services [[electronic resource] ] : 20th International Conference, I4CS 2020, Bhubaneswar, India, January 12–14, 2020, Proceedings / / edited by Siddharth Swarup Rautaray, Gerald Eichler, Christian Erfurth, Günter Fahrnberger |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xiii, 325 pages) : illustrations |
| Disciplina | 004.36 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Computer communication systems
Computers Architecture, Computer Special purpose computers Coding theory Information theory Software engineering Computer Communication Networks Information Systems and Communication Service Computer System Implementation Special Purpose and Application-Based Systems Coding and Information Theory Software Engineering |
| ISBN | 3-030-37484-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996465458603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Machine learning : theoretical foundations and practical applications / / Manjusha Pandey, Siddharth Swarup Rautaray, editors
| Machine learning : theoretical foundations and practical applications / / Manjusha Pandey, Siddharth Swarup Rautaray, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (xi, 172 pages) : illustrations (some color), charts |
| Disciplina | 006.31 |
| Collana | Studies in Big Data |
| Soggetto topico | Machine learning |
| ISBN | 981-336-518-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | What do RDMs capture in brain responses and computational models? -- Challenges and solutions in developing convolutional neural networks and long short-term memory networks for industry problems -- Speed, cloth and pose invariant gait recognition-based person identification -- Application of machine learning in industry 4.0 -- Web semantics and knowledge graph -- Machine learning-based wireless sensor networks -- AI to machine learning : lifeless automation and issues -- Analysis of FDIs in different sectors of the Indian economy -- Customer profiling and retention using recommendation system and factor identification to predict customer churn in telecom industry. |
| Record Nr. | UNINA-9910484871303321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Progress in computing, analytics and networking : proceedings of ICCAN 2019 / / editors, Himansu Das [et al.]
| Progress in computing, analytics and networking : proceedings of ICCAN 2019 / / editors, Himansu Das [et al.] |
| Edizione | [1st edition 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (665 pages) |
| Disciplina | 621.39 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico | Computer science |
| ISBN | 981-15-2414-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Implementation of Session to Mobility Ratio Based Mobility Management Scheme for Wireless Mesh Network to Handle Internet and Intranet Packets -- Peer Analysis of “Sanguj” with Other Sanskrit Morphological Analyzers -- Optimizing Performance of Text Searching using CPU and GPUs -- Partial Offloading for Fog Computing Using P2P Based File Sharing Protocol -- Analysis of Proactive Simulated Topology Reconfiguration for WDM Networks -- Industrial Automation: Case Study - Vision Based Live Object Monitoring System -- Control of Home Appliances and Projector by Smart application using SEAP Protocol -- Maize Leaf Disease Detection and Classification using Machine Learning Algorithms. |
| Record Nr. | UNINA-9910483668903321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Progress in Computing, Analytics and Networking [[electronic resource] ] : Proceedings of ICCAN 2017 / / edited by Prasant Kumar Pattnaik, Siddharth Swarup Rautaray, Himansu Das, Janmenjoy Nayak
| Progress in Computing, Analytics and Networking [[electronic resource] ] : Proceedings of ICCAN 2017 / / edited by Prasant Kumar Pattnaik, Siddharth Swarup Rautaray, Himansu Das, Janmenjoy Nayak |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (826 pages) |
| Disciplina | 004.6 |
| Collana | Advances in Intelligent Systems and Computing |
| Soggetto topico |
Computational intelligence
Signal processing Image processing Speech processing systems Electrical engineering Big data Computational Intelligence Signal, Image and Speech Processing Communications Engineering, Networks Big Data/Analytics |
| ISBN | 981-10-7871-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Preface -- Organizing Committee -- About the Editors -- Table of Contents -- 79 Papers -- Author Index. |
| Record Nr. | UNINA-9910299900903321 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Trends of data science and applications : theory and practices / / Siddharth Swarup Rautaray, Phani Pemmaraju, Hrushikesha Mohanty, editors
| Trends of data science and applications : theory and practices / / Siddharth Swarup Rautaray, Phani Pemmaraju, Hrushikesha Mohanty, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (xiii, 341 pages) : illustrations |
| Disciplina | 006.312 |
| Collana | Studies in computational intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Machine learning |
| ISBN | 981-336-815-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- About This Book -- Contents -- About the Editors -- NLP for Sentiment Computation -- 1 Introduction -- 2 Natural Language and Sentiments -- 3 Lexical Based -- 4 Corpora Based -- 5 Aspect Based -- 6 Trends -- 6.1 Social Semantic -- 6.2 Multi Domain -- 7 Conclusion -- References -- Productizing an Artificial Intelligence Solution for Intelligent Detail Extraction-Synergy of Symbolic and Sub-Symbolic Artificial Intelligence Techniques -- 1 Introduction -- 2 Problem Description of Intelligent Detail Extraction -- 3 Components of an IDE -- 4 Survey of Work on Extraction of Characters -- 5 Case Study: Invoice Processing -- 5.1 Details -- 5.2 Architecture -- 5.3 Challenges -- 5.4 Insight -- 5.5 Discovery and Productizing -- 6 Results and Conclusion -- References -- Digital Consumption Pattern and Impacts of Social Media: Descriptive Statistical Analysis -- 1 Introduction -- 2 Review of Literature -- 3 Access of Internet Across Generations -- 4 Impact of Internet on Business-Management -- 5 Impact of Internet on Kids, Adolescents and Adults -- 6 Internet Service Providers (ISP) in India During This COVID-19 Lockdown -- 7 Objective and Methodology of Primary Data Collection -- 8 Data Analysis -- 9 Bi-variate Analysis -- 10 Conclusion -- References -- Applicational Statistics in Data Science and Machine Learning -- 1 Introduction -- 1.1 Statistics and Exploratory Data Analysis -- 1.2 Statistical Tools and Techniques -- 2 Sampling Techniques -- 2.1 Population Versus Sample -- 2.2 Sampling Methods -- 3 Types of Variables -- 3.1 Random Variable -- 3.2 Categorical Data -- 3.3 Numerical Data -- 3.4 Qualitative Data -- 3.5 Quantitative Data -- 4 Visualizing Data -- 4.1 Categorical Data -- 4.2 Numerical Data -- 5 Measures of Central Tendency -- 5.1 Mean -- 5.2 Median -- 5.3 Mode -- 5.4 Variance -- 5.5 Standard Deviation.
6 Distributions in Statistics -- 6.1 Probability Distributions -- 6.2 PMF Versus PDF -- 6.3 Common Probability Distributions -- 6.4 Kurtosis -- 6.5 Skewness in Distributions -- 6.6 Scaling and Transformations -- 7 Outlier Treatment -- 7.1 Understanding Outliers -- 7.2 Detecting Outliers -- 8 Correlation Analysis -- 8.1 Steps for Correlation Analysis -- 8.2 Autocorrelation Versus Partial Correlation -- 9 Variance and Covariance Analysis -- 9.1 Analysis of Variance (ANOVA) -- 9.2 Analysis of Covariance (ANCOVA) -- 9.3 Multiple Analysis of Variance (MANOVA) -- 9.4 Multiple Analysis of Covariance (MANCOVA) -- 10 Chi-Square Analysis -- 11 Z-Score -- 12 Bias Versus Variance -- 12.1 Bias-Variance Trade-Off -- 12.2 Overfitting and Underfitting -- 13 Hypothesis Testing -- 13.1 Errors in Hypothesis Testing -- 14 Conclusion -- References -- Evolutionary Algorithms-Based Machine Learning Models -- 1 Introduction -- 2 Application Domains -- 2.1 Engineering Applications -- 2.2 Applied Sciences -- 2.3 Disaster Management -- 2.4 Finance and Economy -- 2.5 Health -- 3 Analysis and Discussion -- 3.1 Issues -- 3.2 Gap Analysis -- 4 Conclusion -- References -- Application to Predict the Impact of COVID-19 in India Using Deep Learning -- 1 Introduction -- 2 Proposed Work -- 3 Proposed Modules -- 4 Deep Learning -- 4.1 CNN Model -- 5 System Implementation -- 5.1 Decomposition of the COVID-19 Data -- 6 Results and Analysis -- 7 Conclusion and Future Direction -- References -- Role of Data Analytics in Bio Cyber Physical Systems -- 1 Introduction -- 2 Cyber Physical Systems -- 2.1 CPS and IoT -- 2.2 Concept Map of Cyber Physical Systems -- 2.3 Bio Cyber Physical Systems -- 3 Health Wearables -- 3.1 Fitness Trackers/Smart Watches -- 3.2 Types of Sensors -- 3.3 Activity Log -- 3.4 Advanced Sensors -- 3.5 Data Gathering -- 4 Diabetes -- 4.1 Complications of Diabetes. 5 Case Studies of Diabetic Complications -- 5.1 Heart-Attack -- 5.2 Seizures and Strokes -- 6 Role of Neural Networks in the Case Scenarios -- 6.1 Convolutional Neural Network -- 7 Multi-channel CNN -- 8 Complication Prediction Through LSTM -- 9 Conclusion -- References -- Evolution of Sentiment Analysis: Methodologies and Paradigms -- 1 Introduction -- 2 Foundational Methods -- 2.1 Supervised -- 2.2 Unsupervised and Semi-supervised -- 3 Applications -- 4 Comparative Study -- 4.1 Convolutional and Recurrent Neural Network (with LSTMs) -- 4.2 Word Embeddings/Representations -- 4.3 Deep Belief Networks -- 4.4 Rule-Based and Other Classifiers -- 5 Latest Developments and State-of-the-Art -- 5.1 Transfer Learning and Language Models -- 5.2 Attention and the Transformer -- 5.3 Transformers-Based Architectures -- 5.4 Limits of Transfer Learning -- 6 Conclusions -- References -- Healthcare Analytics: An Advent to Mitigate the Risks and Impacts of a Pandemic -- 1 Introduction -- 1.1 Healthcare Sector -- 1.2 Analytics Domain -- 1.3 Application of Analytics in Healthcare Domain -- 2 Background -- 3 Research on Pandemics and Their Impacts -- 4 Development of Healthcare Information System and Healthcare Analytics -- 5 Results -- 6 Illustration -- 7 Conclusion -- References -- Image Classification for Binary Classes Using Deep Convolutional Neural Network: An Experimental Study -- 1 Introduction -- 2 The Dataset -- 3 Literature Review -- 4 Architecture, Methodology, and Results -- 5 Conclusion -- References -- Leveraging Analytics for Supply Chain Optimization in Freight Industry -- 1 Introduction -- 2 Literature Survey -- 3 Data Storage and Big Data Ecosystem -- 4 Data Processing and Manipulation -- 5 Analytics and Insights -- 6 Machine Learning Implementation -- 6.1 Demand-Supply Matchmaking -- 6.2 Pricing and Incentives. 6.3 User Segmentations to Understand User Activities -- 7 Comparative Study of Different Techniques -- 8 Chapter Takeaways and Significance -- 9 Conclusion and Future Scope -- References -- Trends and Application of Data Science in Bioinformatics -- 1 Introduction -- 2 Data Science -- 3 Application of Data Science in Bioinformatics -- 3.1 Genomics -- 3.2 Transcriptomics -- 3.3 Proteomics -- 3.4 Metabolomics -- 3.5 Epigenetics -- 4 Techniques in Data Science that Can Be Used for Bioinformatics -- 4.1 Machine Learning and Deep Learning -- 4.2 Parallel Computing -- 4.3 Cloud Computing -- 5 Future Perspectives -- 6 Conclusion -- References -- Mathematical and Algorithmic Aspects of Scalable Machine Learning -- 1 Introduction -- 1.1 Challenges in Scalable Machine Learning -- 1.2 Reasons for Scaling up Machine Learning -- 2 The Infrastructure of Scalable Machine Learning -- 2.1 Distributed File System -- 2.2 Distributed Topology for Machine Learning -- 3 MapReduce -- 3.1 Benefits of MapReduce -- 4 Linear Regression -- 4.1 Parallel Version of Linear Regression -- 5 Clustering -- 5.1 K-Mean Clustering -- 5.2 Parallel K-mean for a Scalable Environment -- 5.3 DBSCAN -- 5.4 Parallel DBSCAN -- 6 Parallelization of Support Vector Machine -- 7 Decision Tree -- 8 Conclusion -- References -- An Implementation of Text Mining Decision Feedback Model Using Hadoop MapReduce -- 1 Introduction -- 1.1 Conventional Process Flow of Text Mining -- 1.2 Applications of Text Mining -- 2 Literature Survey -- 3 Proposed Decision Feedback-Based Text Mining Model -- 4 Big Data Technologies -- 4.1 Hadoop Distributed File System -- 4.2 MapReduce -- 4.3 Pig -- 4.4 Hive -- 4.5 Sqoop -- 4.6 Oozie -- 4.7 Flume -- 4.8 ZooKeeper -- 5 Word Stemming -- 5.1 Pre-requisites for Stemming -- 5.2 Classification of Stemming -- 6 Proposed Porter Stemmer with Partitioner Algorithm (PSP). 7 Hadoop Cluster Operation Modes -- 8 Environment Setup -- 9 Implementation -- 9.1 Data Collection -- 9.2 Text Parsing -- 9.3 Text Filtering -- 9.4 Text Transformation -- 9.5 Feature Selection -- 9.6 Evaluate -- 10 Result and Discussion -- 11 Conclusion and Future Work -- References -- Business Analytics: Process and Practical Applications -- 1 Introduction -- 1.1 Definition -- 1.2 Goal -- 2 Process -- 2.1 CRISP-DM (Cross-Industry Standard Process for Data Mining) -- 2.2 SEMMA (Sample, Explore, Modify, Model, Assess) -- 2.3 Comparative Study -- 2.4 Others Approaches -- 3 Types of Analytics -- 3.1 Descriptive Analytics -- 3.2 Diagnostic Analytics -- 3.3 Predictive Analytics -- 3.4 Prescriptive Analytics -- 3.5 Comparative Study -- 4 Domain and Applications -- 5 Recommendation System(s)-An approach -- 5.1 Types of Recommendation Systems -- 5.2 Benefits of Recommendation System -- 5.3 An Example -- 5.4 Challenges of Recommendation Systems -- 5.5 Comparative Study -- 6 Tools -- 7 Conclusion -- References -- Challenges and Issues of Recommender System for Big Data Applications -- 1 Introduction -- 1.1 Recommendation System Architecture -- 1.2 Big Data -- 2 The Cold Start Problem in Recommendation -- 2.1 New User Cold Start Problem -- 2.2 New Item Cold Start Problem -- 3 Scalability -- 3.1 Scalable Neighborhood Algorithm -- 4 Proactive Recommender System -- 4.1 Proactive Recommendation -- 4.2 Intelligent Proactive Recommender System -- 5 Conclusion -- References. |
| Record Nr. | UNINA-9910485004303321 |
| Singapore : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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