Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Blended Learning. Intelligent Computing in Education : 17th International Conference on Blended Learning, ICBL 2024, Macao SAR, China, July 29 - August 1, 2024, Proceedings
| Blended Learning. Intelligent Computing in Education : 17th International Conference on Blended Learning, ICBL 2024, Macao SAR, China, July 29 - August 1, 2024, Proceedings |
| Autore | Ma Will W. K |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2024 |
| Descrizione fisica | 1 online resource (355 pages) |
| Altri autori (Persone) |
LiChen
FanChun Wai ULeong Hou LuAngel |
| Collana | Lecture Notes in Computer Science Series |
| ISBN | 9789819744428 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Contents -- Keynotes -- Building a Learner-Centric Citywide Digital Literacy Ecosystem: Train-the-Trainer, Community-Based Learning, and Gifted Education -- 1 Introduction -- 2 What is a Learner-Centric Citywide Digital Literacy Ecosystem? -- 3 What are the Benefits of Building a Learner-Centric Citywide Digital Literacy Ecosystem? -- 4 What are the Challenges of Building a Learner-Centric Citywide Digital Literacy Ecosystem? -- 5 How Can Train-the-Trainer, Community-Based Learning, and Gifted Education Approaches Support Building a Learner-Centric Citywide Digital Literacy Ecosystem? -- 6 Use Case 1: HKSAR Gifted Education Programme -- 6.1 What is It? -- 6.2 What Has Been Taught? -- 6.3 Short-Term Results -- 6.4 Long-Term Results -- 6.5 Challenges and Recommendations for Improvement -- 7 Use Case 2: CityU Apps Lab (CAL) Train-the-Trainer City-Wide Programme -- 7.1 CityU Apps Lab Programs -- 7.2 Apps Lab's Problem-Based Learning Method -- 7.3 Students Achievements -- 7.4 Apps Lab Students Feedback -- 8 Conclusions -- References -- Trends and Challenges in Digital Education in the Age of Artificial Intelligence -- 1 Introduction -- 2 Overcoming Myths About Using Technology in Education -- 3 Educational Technology Trends in the AI Era -- 3.1 A Need for Increased Personalization of Educational Processes -- 3.2 Integration with Educational Uses of Virtual Reality (VR) and Augmented Reality (AR) -- 3.3 Improved Educational Feedback -- 3.4 Ethics and Improved Bias in Results -- 3.5 Educational Lifelong Learning Trajectories -- 4 Generative AI's Main Future Challenges -- 4.1 Adaptive Systems and Personalization -- 4.2 Profiling and Prediction -- 4.3 Assessment and Evaluation -- 4.4 Intelligent Tutoring Systems (ITS) -- 5 AI in HE: Ethical and Social Implications -- References.
How to Design Scientific, Happy and Effective Educational Games: Research on Educational Game Design from the Perspective of Learning Sciences -- 1 Introduction -- 2 Rationale for the Design of Educational Games -- 2.1 Theoretically Based on Research Findings in Educational Neuroscience -- 2.2 Technically Supported by Research Findings in Learning Analytics -- 3 Cases of Educational Game Design -- 3.1 The Arithmetic Game Monster Blocks -- 3.2 The Fraction Game Run Fraction -- 3.3 The Spatial Game Cube Elimination -- 3.4 The Number Cognition Game Find Stars -- 4 Characterization and Design Model of Educational Games -- 4.1 Characterization of Educational Games -- 4.2 Design Model for Educational Games -- 5 Design Principles of Educational Games -- 5.1 Balance of Skills and Challenges -- 5.2 Balance of Education and Game -- 5.3 Balance of Theory and Practice -- 5.4 Balance of Individuality and Commonality -- 6 Conclusion -- References -- Blended Learning and AI: Enhancing Teaching and Learning in Higher Education -- 1 Introduction -- 2 A Survey of Recent Scholarship on GenAI and BL -- 2.1 GenAI in Higher Education -- 2.2 GenAI in BL -- 3 Discussion: Observations and Strategies -- 3.1 AI Readiness, Literacy and Competency -- 3.2 Professional Development for Instructors -- 3.3 Learners' Use and Perception -- 3.4 Learning Analytics -- 3.5 Infrastructure -- 3.6 Co-Regulation -- 3.7 Copyright -- 3.8 Data Privacy -- 3.9 Inclusivity and Accessibility -- 4 Conclusion -- References -- Digital Literacy: Evolution, Evaluation and Enhancement -- 1 Introduction -- 2 Literature Review -- 2.1 Connotation Development of Digital Literacy -- 2.2 Connotation Development of Digital Literacy -- 3 Evaluation of Chinese Students' Digital Literacy -- 3.1 Sample Selection -- 3.2 Research Instrument -- 3.3 Results -- 4 Recommendations for Enhancing Students' Digital Literacy. 4.1 Building a Multi-Body Synergistic System to Cultivate Students' Digital Literacy -- 4.2 Exploring a Comprehensive Cultivation System for Students' Digital Literacy -- 4.3 Creating a Data-Driven Assessment System for Students' Digital Literacy -- References -- Revolutionizing Education with AI -- Complexities of Using Large Language Model Generative AI in Health Education and Robots -- 1 Introduction -- 2 Case Studies Using GPT3.5 (Accessed 01.28.2024) -- 2.1 Teaching the Human Circulatory System to Students in an American High School Grade 10 -- 2.2 Teaching Complex Health Issues Related to Blood Circulation in a Required Pathophysiology Course for American Undergraduate Students Applying to an American Bachelor of Science in Nursing Program -- 3 Discussion -- 4 Related Ongoing and Future Research Directions -- References -- New Dimensions: The Impact of the Metaverse and AI Avatars on Social Science Education -- 1 Introduction -- 2 Method -- 3 Results -- 4 Discussion -- 4.1 The Role of 'Interesting' in Predicting Intent to Use the Metaverse -- 4.2 Environment Topics Are More Usable and There is a Statistical Relationship Between Performance, Usefulness, and Interest -- 4.3 Environments with AI Avatars Are Less Easy to Use -- 4.4 Implications of Regression Findings -- 4.5 Comparison with Existing Works -- 4.6 Limitations -- 5 Conclusion -- References -- Construction and Implementation of Generative AI-Based Human-Machine Collaborative Classroom Teaching Model in Universities -- 1 Introduction -- 2 Literature Review -- 2.1 A Review of Research on the Application of GAI in University Classroom Teaching -- 2.2 A Review of Research on Human-Machine Collaboration Classroom Teaching -- 3 Research Design and Research Methods -- 3.1 Status Investigation -- 3.2 Theoretical Analysis -- 3.3 Model Construction -- 3.4 Model Implementation. 3.5 Effectiveness Evaluation -- 4 The Construction of GAI-Based Human-Machine Collaborative Classroom Teaching Model in Universities -- 4.1 Main Theoretical Basis -- 4.2 The Connotation Elements of GAI-based Human-Machine Collaborative Classroom in Universities -- 4.3 The Teaching Mechanism of GAI-based Human-Machine Collaborative Classroom in Universities -- 4.4 The Construction of GAI-based Human-Machine Collaborative SOCAEE Classroom Teaching Model in Universities -- 5 The Implementation of GAI-Based Human-Machine Collaborative SOCAEE Classroom Teaching Model in Universities -- 5.1 The Overview of Research Implementation -- 5.2 The First Round of Action Research -- 5.3 The Second Round of Action Research -- 6 Research Effect -- 6.1 Students' Classroom Learning Performance -- 6.2 Students' Human-Machine Collaborative Learning Ability -- 6.3 Students' Human-Machine Collaborative Learning Experience -- 7 Discussion -- 8 Conclusion -- References -- DMPAI: An AI-Aided K-12 System for Teaching and Learning in Diverse Schools -- 1 Introduction -- 2 Related Work -- 2.1 Predictive Analysis -- 2.2 Early Warning System (EWS) -- 2.3 Learning Analytics -- 2.4 Talented/Gifted Students Prediction and Identification -- 2.5 Recommender System -- 3 Methodology -- 3.1 Student Academic Performance and Behavior Prediction and Intervention -- 3.2 Early Warning System -- 3.3 Analytics of Individualized Education Plan (IEP) -- 3.4 Talented Students' Prediction and Identification -- 3.5 Cross-School Personalized Electives Recommendation -- 4 Results -- 5 Conclusion -- References -- A Case Study Examines How a New Content Integration Impacts Learning Outcomes with AI Experience Inputs -- 1 Introduction -- 2 Background -- 2.1 Targets for Higher Education -- 2.2 Shaping of Teaching Characteristics -- 2.3 Promotion of AI Courses. 2.4 Integrating AI Content into Existing Curriculum -- 3 CG/CAD Courses and the Study -- 3.1 Digital Applications in Architecture -- 3.2 Initial Ideas for Incorporating AI -- 3.3 Execution of AI Experiential Learning -- 4 Research Method -- 5 Results and Discussions -- 5.1 Usability Surveys on AI Only -- 5.2 Comprehensive Quiz Scores -- 5.3 Focus Group Interviews -- 5.4 Discussion and Recommendations -- 6 Limitations and Conclusions -- References -- Blended Learning and Technological Innovations -- Understanding Characteristics of Teacher-Student Dialogue in Urban-Rural Blended Synchronous Classroom: A Learning Analytics Perspective -- 1 Introduction -- 2 Theoretical Framework -- 3 Method -- 3.1 Research Sample -- 3.2 Data Collection -- 3.3 Data Analysis -- 4 Result -- 4.1 Characteristics in Teacher-Student Dialogue in Two Types of Urban-Rural Synchronous Classrooms Taught by Different Teachers -- 4.2 Analysis of the Characteristics of Teacher-Questioning Behavior Transitions in Two Types of Classrooms Taught by Different Teachers -- 4.3 Analysis of Key Teacher Questioning Behaviors in Two Types of Classrooms Taught by Different Teachers -- 5 Discussion -- 5.1 The Frequency of Teacher-Student Dialogue Interaction of the Two Types of BSC Was not Well Balanced -- 5.2 The Cognitive Level of Teacher-Student Dialogue of the Two Types of BSC Mainly Remained at the Level of Understanding -- 5.3 The Teacher Questioning Behavior Transition Characteristics of the Two Types of Classrooms Were Different -- 6 Implications -- 7 Conclusions -- References -- Integrating a Digital Math Vector Game into a Blended Classroom: Technological and Instructional Design Principles -- 1 Introduction -- 2 Theoretical Framework -- 2.1 Vector Learning Difficulty -- 2.2 Digital Vector Game -- 2.3 Blended Classroom Integrating Digital Game -- 2.4 GoVector: A Digital Math Game. 3 Research Design. |
| Record Nr. | UNINA-9910869182203321 |
Ma Will W. K
|
||
| Singapore : , : Springer Singapore Pte. Limited, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Trends and Applications in Knowledge Discovery and Data Mining [[electronic resource] ] : PAKDD 2019 Workshops, BDM, DLKT, LDRC, PAISI, WeL, Macau, China, April 14–17, 2019, Revised Selected Papers / / edited by Leong Hou U., Hady W. Lauw
| Trends and Applications in Knowledge Discovery and Data Mining [[electronic resource] ] : PAKDD 2019 Workshops, BDM, DLKT, LDRC, PAISI, WeL, Macau, China, April 14–17, 2019, Revised Selected Papers / / edited by Leong Hou U., Hady W. Lauw |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIII, 366 p. 162 illus., 115 illus. in color.) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Application software Data mining Optical data processing Data protection Artificial Intelligence Information Systems Applications (incl. Internet) Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Appl. in Social and Behavioral Sciences Security |
| ISBN | 3-030-26142-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2019) -- A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045 -- An Investigation on Multi View based User Behavior towards Spam Detection in Social Networks -- A Cluster Ensemble Strategy for Asian Handicap Betting -- Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example -- Early Churn User Classification in Social Networking Service Using Attention-based Long Short-Term Memory -- PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019) -- Weakly Supervised Learning by a Confusion Matrix of Contexts -- Learning a Semantic Space for Modeling Images,Tags and Feelings in Cross-media Search -- Adversarial Active Learning in the Presence of Weak and Malicious Oracles -- The Most Related Knowledge First: A Progressive Domain Adaptation Method -- Learning Data Representation for Clustering (LDRC 2019) -- Deep Architectures for Joint Clustering and Visualization with Self-Organizing Maps -- Deep cascade of extra trees -- Algorithms for an Efficient Tensor Biclustering -- Change point detetion in periodic panel data using a mixture-model-based approach -- The 8th Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining (BDM 2019) -- Neural Network-Based Deep Encoding for Mixed-Attribute Data Classification -- Protein Complexes Detection Based on Deep Neural Network -- Predicting Auction Price of Vehicle License Plate with Deep Residual Learning -- Mining Multispectral Aerial Images for Automatic Detection of Strategic Bridge Locations for Disaster Relief Missions -- Chinese Word Segmentation with Feature Alignment -- Spike Sorting with Locally Weighted Co-association Matrix-based Spectral Clustering -- Label Distribution Learning Based Age-Invariant Face Recognition -- Overall Loss For Deep Neural Networks -- Sentiment Analysis Based on LSTM Architecture with Emoticon Attention -- Aspect Level Sentiment Analysis with Aspect Attention -- The 1st Pacific Asia Workshop on Deep Learning for Knowledge Transfer (DLKT 2019) -- Transfer Channel Pruning for Compressing Deep Domain Adaptation Models -- A Heterogeneous Domain Adversarial Neural Network for Trans-Domain Behavioral Targeting -- Natural Language Business Intelligence Question Answering through SeqtoSeq Transfer Learning -- Robust Faster R-CNN:Increasing Robustness to Occlusions and multi-scale objects -- Effectively Representing Short Text via the Improved Semantic Feature Space Mapping -- Probabilistic Graphical Model Based Highly Scalable Directed Community Detection Algorithm -- Hilltop based recommendation in co-author networks -- Neural Variational Collaborative Filtering for Top-K Recommendation. . |
| Record Nr. | UNISA-996466311303316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Trends and Applications in Knowledge Discovery and Data Mining : PAKDD 2019 Workshops, BDM, DLKT, LDRC, PAISI, WeL, Macau, China, April 14–17, 2019, Revised Selected Papers / / edited by Leong Hou U., Hady W. Lauw
| Trends and Applications in Knowledge Discovery and Data Mining : PAKDD 2019 Workshops, BDM, DLKT, LDRC, PAISI, WeL, Macau, China, April 14–17, 2019, Revised Selected Papers / / edited by Leong Hou U., Hady W. Lauw |
| Edizione | [1st ed. 2019.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
| Descrizione fisica | 1 online resource (XIII, 366 p. 162 illus., 115 illus. in color.) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Application software Data mining Optical data processing Data protection Artificial Intelligence Information Systems Applications (incl. Internet) Data Mining and Knowledge Discovery Image Processing and Computer Vision Computer Appl. in Social and Behavioral Sciences Security |
| ISBN | 3-030-26142-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 14th Pacific Asia Workshop on Intelligence and Security Informatics (PAISI 2019) -- A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045 -- An Investigation on Multi View based User Behavior towards Spam Detection in Social Networks -- A Cluster Ensemble Strategy for Asian Handicap Betting -- Designing an Integrated Intelligence Center: New Taipei City Police Department as an Example -- Early Churn User Classification in Social Networking Service Using Attention-based Long Short-Term Memory -- PAKDD 2019 Workshop on Weakly Supervised Learning: Progress and Future (WeL 2019) -- Weakly Supervised Learning by a Confusion Matrix of Contexts -- Learning a Semantic Space for Modeling Images,Tags and Feelings in Cross-media Search -- Adversarial Active Learning in the Presence of Weak and Malicious Oracles -- The Most Related Knowledge First: A Progressive Domain Adaptation Method -- Learning Data Representation for Clustering (LDRC 2019) -- Deep Architectures for Joint Clustering and Visualization with Self-Organizing Maps -- Deep cascade of extra trees -- Algorithms for an Efficient Tensor Biclustering -- Change point detetion in periodic panel data using a mixture-model-based approach -- The 8th Workshop on Biologically-inspired Techniques for Knowledge Discovery and Data Mining (BDM 2019) -- Neural Network-Based Deep Encoding for Mixed-Attribute Data Classification -- Protein Complexes Detection Based on Deep Neural Network -- Predicting Auction Price of Vehicle License Plate with Deep Residual Learning -- Mining Multispectral Aerial Images for Automatic Detection of Strategic Bridge Locations for Disaster Relief Missions -- Chinese Word Segmentation with Feature Alignment -- Spike Sorting with Locally Weighted Co-association Matrix-based Spectral Clustering -- Label Distribution Learning Based Age-Invariant Face Recognition -- Overall Loss For Deep Neural Networks -- Sentiment Analysis Based on LSTM Architecture with Emoticon Attention -- Aspect Level Sentiment Analysis with Aspect Attention -- The 1st Pacific Asia Workshop on Deep Learning for Knowledge Transfer (DLKT 2019) -- Transfer Channel Pruning for Compressing Deep Domain Adaptation Models -- A Heterogeneous Domain Adversarial Neural Network for Trans-Domain Behavioral Targeting -- Natural Language Business Intelligence Question Answering through SeqtoSeq Transfer Learning -- Robust Faster R-CNN:Increasing Robustness to Occlusions and multi-scale objects -- Effectively Representing Short Text via the Improved Semantic Feature Space Mapping -- Probabilistic Graphical Model Based Highly Scalable Directed Community Detection Algorithm -- Hilltop based recommendation in co-author networks -- Neural Variational Collaborative Filtering for Top-K Recommendation. . |
| Record Nr. | UNINA-9910349298003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Web and big data . Part II : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors)
| Web and big data . Part II : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (471 pages) |
| Disciplina | 005.7 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Big data |
| ISBN | 3-030-85899-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910495228503321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Web and big data . Part I : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors)
| Web and big data . Part I : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (513 pages) |
| Disciplina | 005.7 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Big data |
| ISBN | 3-030-85896-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910495228303321 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Web and big data . Part II : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors)
| Web and big data . Part II : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (471 pages) |
| Disciplina | 005.7 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Big data |
| ISBN | 3-030-85899-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464394003316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Web and big data . Part I : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors)
| Web and big data . Part I : 5th international joint conference, APWeb-WAIM 2021, Guangzhou, China, August 23-25, 2021 : proceedings / / Leong Hou U [and three others] (editors) |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (513 pages) |
| Disciplina | 005.7 |
| Collana | Lecture notes in computer science |
| Soggetto topico | Big data |
| ISBN | 3-030-85896-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464393303316 |
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Web and Big Data [[electronic resource] ] : APWeb-WAIM 2018 International Workshops: MWDA, BAH, KGMA, DMMOOC, DS, Macau, China, July 23–25, 2018, Revised Selected Papers / / edited by Leong Hou U, Haoran Xie
| Web and Big Data [[electronic resource] ] : APWeb-WAIM 2018 International Workshops: MWDA, BAH, KGMA, DMMOOC, DS, Macau, China, July 23–25, 2018, Revised Selected Papers / / edited by Leong Hou U, Haoran Xie |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIII, 394 p. 144 illus.) |
| Disciplina | 004.678 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Information storage and retrieval
Data mining Application software Artificial intelligence Natural language processing (Computer science) Special purpose computers Information Storage and Retrieval Data Mining and Knowledge Discovery Information Systems Applications (incl. Internet) Artificial Intelligence Natural Language Processing (NLP) Special Purpose and Application-Based Systems |
| ISBN | 3-030-01298-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Mobile web data analytics -- Big data analytics for healthcare -- Knowledge graph management and analysis -- Data management and mining on MOOCs -- Data science. . |
| Record Nr. | UNISA-996466278603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Web and Big Data : APWeb-WAIM 2018 International Workshops: MWDA, BAH, KGMA, DMMOOC, DS, Macau, China, July 23–25, 2018, Revised Selected Papers / / edited by Leong Hou U, Haoran Xie
| Web and Big Data : APWeb-WAIM 2018 International Workshops: MWDA, BAH, KGMA, DMMOOC, DS, Macau, China, July 23–25, 2018, Revised Selected Papers / / edited by Leong Hou U, Haoran Xie |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XIII, 394 p. 144 illus.) |
| Disciplina | 004.678 |
| Collana | Information Systems and Applications, incl. Internet/Web, and HCI |
| Soggetto topico |
Information storage and retrieval
Data mining Application software Artificial intelligence Natural language processing (Computer science) Special purpose computers Information Storage and Retrieval Data Mining and Knowledge Discovery Information Systems Applications (incl. Internet) Artificial Intelligence Natural Language Processing (NLP) Special Purpose and Application-Based Systems |
| ISBN | 3-030-01298-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Mobile web data analytics -- Big data analytics for healthcare -- Knowledge graph management and analysis -- Data management and mining on MOOCs -- Data science. . |
| Record Nr. | UNINA-9910349394503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Web Information Systems Engineering [[electronic resource] ] : WISE 2019 Workshop, Demo, and Tutorial, Hong Kong and Macau, China, January 19–22, 2020, Revised Selected Papers / / edited by Leong Hou U, Jian Yang, Yi Cai, Kamalakar Karlapalem, An Liu, Xin Huang
| Web Information Systems Engineering [[electronic resource] ] : WISE 2019 Workshop, Demo, and Tutorial, Hong Kong and Macau, China, January 19–22, 2020, Revised Selected Papers / / edited by Leong Hou U, Jian Yang, Yi Cai, Kamalakar Karlapalem, An Liu, Xin Huang |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (VIII, 185 p. 76 illus., 63 illus. in color.) |
| Disciplina | 620.7 |
| Collana | Communications in Computer and Information Science |
| Soggetto topico |
Application software
Database management Computer organization Data structures (Computer science) Artificial intelligence Information Systems Applications (incl. Internet) Database Management Computer Systems Organization and Communication Networks Data Structures and Information Theory Computer Appl. in Social and Behavioral Sciences Artificial Intelligence |
| ISBN | 981-15-3281-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Tutorials -- Demos -- The International Workshop on Web Information Systems in the Era of AI. |
| Record Nr. | UNISA-996465352203316 |
| Singapore : , : Springer Singapore : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
