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Autor Cong, Gao |
Documentos disponibles escritos por este autor (2)
Crear una solicitud de compra Refinar búsquedaAdvanced Data Mining and Applications / Cong, Gao ; Peng, Wen-Chih ; Zhang, Wei Emma ; Li, Chengliang ; Sun, Aixin
TÃtulo : Advanced Data Mining and Applications : 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings / Tipo de documento: documento electrónico Autores: Cong, Gao, ; Peng, Wen-Chih, ; Zhang, Wei Emma, ; Li, Chengliang, ; Sun, Aixin, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2017 Número de páginas: XVII, 881 p. 264 ilustraciones ISBN/ISSN/DL: 978-3-319-69179-4 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Inteligencia artificial Procesamiento de datos Sistemas de almacenamiento y recuperación de información. Software de la aplicacion Procesamiento del lenguaje natural (Informática) Red de computadoras MinerÃa de datos y descubrimiento de conocimientos Almacenamiento y recuperación de información Aplicaciones informáticas y de sistemas de información Procesamiento del lenguaje natural (PNL) Redes de comunicación informática Clasificación: 006.3 Resumen: Este libro constituye las actas arbitradas de la 13.ª Conferencia Internacional sobre Aplicaciones y MinerÃa de Datos Avanzados, ADMA 2017, celebrada en Singapur en noviembre de 2017. Los 20 artÃculos completos y 38 breves presentados en este volumen fueron cuidadosamente revisados ​​y seleccionados entre 118 presentaciones. Los artÃculos se organizaron en secciones temáticas denominadas: base de datos y aprendizaje automático distribuido; sistema de recomendación; red social y medios sociales; aprendizaje automático; métodos de clasificación y agrupamiento; modelado de comportamiento y elaboración de perfiles de usuarios; bioinformática y análisis de datos médicos; datos espacio-temporales; procesamiento de lenguaje natural y minerÃa de textos; aplicaciones de minerÃa de datos; aplicaciones; y demostraciones. . Nota de contenido: Database and Distributed Machine Learning -- Querying and Mining Strings Made Easy Distributed Training Large-Scale Deep Architectures -- Fault Detection and Localization in Distributed Systems using Recurrent Convolutional Neural Networks -- Discovering Group Skylines with Constraints by Early Candidate Pruning -- Comparing MapReduce-Based k-NN Similarity Joins On Hadoop For High-dimensional Data -- A Higher-Fidelity Frugal Quantile Estimator -- Recommender System -- Fair Recommendations Through Diversity Promotion -- A Hierarchical Bayesian Factorization Model for Implicit and Explicit Feedback Data -- Empirical Analysis of Factors Influencing Twitter Hashtag Recommendation on Detected Communities -- Group Recommender Model Based on Preference Interaction -- Identification of Grey Sheep Users By Histogram Intersection In Recommender Systems -- Social Network and Social Media -- A Feature-based Approach for the Redefined Link Prediction Problem in Signed Networks -- From Mutual Friends to Overlapping Community Detection: A Non-negative Matrix Factorization Approach -- Calling for Response: Automatically Distinguishing Situation-aware Tweets During Crises -- Efficient Revenue Maximization for Viral Marketing in Social Networks -- Generating Life Course Trajectory Sequences with Recurrent Neural Networks and Application to Early Detection on Social Disadvantage -- FRISK: A Multilingual Approach to Find twitteR InterestS via wiKipedia -- A Solution to Tweet-Based User Identification across Online Social Networks -- Machine Learning -- Supervised Feature Selection Algorithm Based on Low-Rank and Manifold Learning -- Mixed Membership Sparse Gaussian Conditional Random Fields -- Effects of Dynamic Subspacing in Random Forest -- Diversity and Locality in Multi-Component, Multi-Layer Predictive Systems: A Mutual Information Based Approach -- Hybrid Subspace Mixture Models For Prediction and Anomaly Detection in High Dimensions -- Classification and Clustering Methods --  StruClus: Scalable Structural Graph Set Clustering with Representative Sampling -- Employing Hierarchical Clustering and Reinforcement Learning for Attribute-based Zero-Shot Classification -- Environmental Sound Recognition using Masked Conditional Neural Networks -- Analyzing Performance of Classification Techniques in Detecting Epileptic Seizure -- A Framework for Clustering and Dynamic Maintenance of XML Documents -- Language-independent Twitter Classification using Character-based Convolutional Networks -- Behavior Modeling and User Profiling -- Modeling Check-in Behavior with Geographical Neighborhood Influence of Venues -- An empirical study on collective online behaviors of extremist supporters. -Your Moves, Your Device: Establishing Behavior Profiles using Tensors -- An Approach for Identifying Author Profiles of Blogs -- Generating Topics of Interests for Research Communities -- An Evolutionary Approach for Learning Conditional Preference Network from Inconsistent Examples -- Bioinformatic and Medical Data Analysis -- Predicting Clinical Outcomes of Alzheimer's Disease from Complex Brain Networks -- Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties -- Multiclass Lung Cancer Diagnosis by Gene Expression Programming and Microarray Datasets -- Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers -- Spatio-temporal Data -- People-Centric Mobile Crowdsensing Platform for Urban Design -- Long-Term User Location Prediction Using Deep Learning and Periodic Pattern Mining -- An Intelligent Weighted Fuzzy Time Series Model Based on A Sine-Cosine Adaptive Human Learning Optimization Algorithm and Its Application to Financial Markets Forecasting -- Mobile Robot Scheduling with Multiple Trips and Time Windows -- Natural Language Processing and Text Mining -- Feature Analysis for Duplicate Detection in Programming QA Communities -- A Joint Human/Machine Process for Coding Events and Conflict Drivers -- Quality Prediction of Newly Proposed Questions in CQA by Leveraging Weakly Supervised Learning -- Improving Chinese Sentiment Analysis via Segmentation-based Representation Using Parallel CNN -- Entity Recognition by Distant Supervision with Soft List Constraint -- Structured Sentiment Analysis -- Data Mining Applications -- Improving Real-Time Bidding Using a Constrained Markov Decision Process -- PowerLSTM: Power Demand Forecasting Using Long Short-Term Memory Neural Network -- Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments -- Color-sketch simulator: a guide for color-based visual known-item search -- Applications -- Making Use of External Company Data to Improve the Classification of Bank Transactions -- Mining Load Profile Patterns for Australian Electricity Consumers -- STA: a Spatio-temporal Thematic Analytics Framework for Urban Ground Sensing -- Privacy and Utility Preservation for Location Data Using Stay Region Analysis -- Location-aware Human Activity Recognition -- Demos -- SWYSWYK: a new Sharing Paradigm for the Personal Cloud -- Tools and Infrastructure for Supporting Enterprise Knowledge Graphs -- An Interactive Web-based Toolset for Knowledge Discovery from Short Text Log Data -- Carbon: Forecasting Civil Unrest Events by Monitoring News and Social Media -- A system for Querying and Analyzing Urban Regions -- Detect tracking behavior among trajectory data. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017. The 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Advanced Data Mining and Applications : 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings / [documento electrónico] / Cong, Gao, ; Peng, Wen-Chih, ; Zhang, Wei Emma, ; Li, Chengliang, ; Sun, Aixin, . - 1 ed. . - [s.l.] : Springer, 2017 . - XVII, 881 p. 264 ilustraciones.
ISBN : 978-3-319-69179-4
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Inteligencia artificial Procesamiento de datos Sistemas de almacenamiento y recuperación de información. Software de la aplicacion Procesamiento del lenguaje natural (Informática) Red de computadoras MinerÃa de datos y descubrimiento de conocimientos Almacenamiento y recuperación de información Aplicaciones informáticas y de sistemas de información Procesamiento del lenguaje natural (PNL) Redes de comunicación informática Clasificación: 006.3 Resumen: Este libro constituye las actas arbitradas de la 13.ª Conferencia Internacional sobre Aplicaciones y MinerÃa de Datos Avanzados, ADMA 2017, celebrada en Singapur en noviembre de 2017. Los 20 artÃculos completos y 38 breves presentados en este volumen fueron cuidadosamente revisados ​​y seleccionados entre 118 presentaciones. Los artÃculos se organizaron en secciones temáticas denominadas: base de datos y aprendizaje automático distribuido; sistema de recomendación; red social y medios sociales; aprendizaje automático; métodos de clasificación y agrupamiento; modelado de comportamiento y elaboración de perfiles de usuarios; bioinformática y análisis de datos médicos; datos espacio-temporales; procesamiento de lenguaje natural y minerÃa de textos; aplicaciones de minerÃa de datos; aplicaciones; y demostraciones. . Nota de contenido: Database and Distributed Machine Learning -- Querying and Mining Strings Made Easy Distributed Training Large-Scale Deep Architectures -- Fault Detection and Localization in Distributed Systems using Recurrent Convolutional Neural Networks -- Discovering Group Skylines with Constraints by Early Candidate Pruning -- Comparing MapReduce-Based k-NN Similarity Joins On Hadoop For High-dimensional Data -- A Higher-Fidelity Frugal Quantile Estimator -- Recommender System -- Fair Recommendations Through Diversity Promotion -- A Hierarchical Bayesian Factorization Model for Implicit and Explicit Feedback Data -- Empirical Analysis of Factors Influencing Twitter Hashtag Recommendation on Detected Communities -- Group Recommender Model Based on Preference Interaction -- Identification of Grey Sheep Users By Histogram Intersection In Recommender Systems -- Social Network and Social Media -- A Feature-based Approach for the Redefined Link Prediction Problem in Signed Networks -- From Mutual Friends to Overlapping Community Detection: A Non-negative Matrix Factorization Approach -- Calling for Response: Automatically Distinguishing Situation-aware Tweets During Crises -- Efficient Revenue Maximization for Viral Marketing in Social Networks -- Generating Life Course Trajectory Sequences with Recurrent Neural Networks and Application to Early Detection on Social Disadvantage -- FRISK: A Multilingual Approach to Find twitteR InterestS via wiKipedia -- A Solution to Tweet-Based User Identification across Online Social Networks -- Machine Learning -- Supervised Feature Selection Algorithm Based on Low-Rank and Manifold Learning -- Mixed Membership Sparse Gaussian Conditional Random Fields -- Effects of Dynamic Subspacing in Random Forest -- Diversity and Locality in Multi-Component, Multi-Layer Predictive Systems: A Mutual Information Based Approach -- Hybrid Subspace Mixture Models For Prediction and Anomaly Detection in High Dimensions -- Classification and Clustering Methods --  StruClus: Scalable Structural Graph Set Clustering with Representative Sampling -- Employing Hierarchical Clustering and Reinforcement Learning for Attribute-based Zero-Shot Classification -- Environmental Sound Recognition using Masked Conditional Neural Networks -- Analyzing Performance of Classification Techniques in Detecting Epileptic Seizure -- A Framework for Clustering and Dynamic Maintenance of XML Documents -- Language-independent Twitter Classification using Character-based Convolutional Networks -- Behavior Modeling and User Profiling -- Modeling Check-in Behavior with Geographical Neighborhood Influence of Venues -- An empirical study on collective online behaviors of extremist supporters. -Your Moves, Your Device: Establishing Behavior Profiles using Tensors -- An Approach for Identifying Author Profiles of Blogs -- Generating Topics of Interests for Research Communities -- An Evolutionary Approach for Learning Conditional Preference Network from Inconsistent Examples -- Bioinformatic and Medical Data Analysis -- Predicting Clinical Outcomes of Alzheimer's Disease from Complex Brain Networks -- Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties -- Multiclass Lung Cancer Diagnosis by Gene Expression Programming and Microarray Datasets -- Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers -- Spatio-temporal Data -- People-Centric Mobile Crowdsensing Platform for Urban Design -- Long-Term User Location Prediction Using Deep Learning and Periodic Pattern Mining -- An Intelligent Weighted Fuzzy Time Series Model Based on A Sine-Cosine Adaptive Human Learning Optimization Algorithm and Its Application to Financial Markets Forecasting -- Mobile Robot Scheduling with Multiple Trips and Time Windows -- Natural Language Processing and Text Mining -- Feature Analysis for Duplicate Detection in Programming QA Communities -- A Joint Human/Machine Process for Coding Events and Conflict Drivers -- Quality Prediction of Newly Proposed Questions in CQA by Leveraging Weakly Supervised Learning -- Improving Chinese Sentiment Analysis via Segmentation-based Representation Using Parallel CNN -- Entity Recognition by Distant Supervision with Soft List Constraint -- Structured Sentiment Analysis -- Data Mining Applications -- Improving Real-Time Bidding Using a Constrained Markov Decision Process -- PowerLSTM: Power Demand Forecasting Using Long Short-Term Memory Neural Network -- Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments -- Color-sketch simulator: a guide for color-based visual known-item search -- Applications -- Making Use of External Company Data to Improve the Classification of Bank Transactions -- Mining Load Profile Patterns for Australian Electricity Consumers -- STA: a Spatio-temporal Thematic Analytics Framework for Urban Ground Sensing -- Privacy and Utility Preservation for Location Data Using Stay Region Analysis -- Location-aware Human Activity Recognition -- Demos -- SWYSWYK: a new Sharing Paradigm for the Personal Cloud -- Tools and Infrastructure for Supporting Enterprise Knowledge Graphs -- An Interactive Web-based Toolset for Knowledge Discovery from Short Text Log Data -- Carbon: Forecasting Civil Unrest Events by Monitoring News and Social Media -- A system for Querying and Analyzing Urban Regions -- Detect tracking behavior among trajectory data. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017. The 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos. . Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
TÃtulo : Databases Theory and Applications : 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings Tipo de documento: documento electrónico Autores: Wang, Junhu, ; Cong, Gao, ; Chen, Jinjun, ; Qi, Jianzhong, Mención de edición: 1 ed. Editorial: [s.l.] : Springer Fecha de publicación: 2018 Número de páginas: XXV, 360 p. 149 ilustraciones ISBN/ISSN/DL: 978-3-319-92013-9 Nota general: Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. Idioma : Inglés (eng) Palabras clave: Gestión de base de datos Procesamiento de datos Software de la aplicacion Inteligencia artificial Ciencias sociales Red de computadoras MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Aplicación informática en ciencias sociales y del comportamiento. Redes de comunicación informática Clasificación: 005.74 Ciencia de los computadores (Archivos de datos y bases de datos) Resumen: Este libro constituye las actas arbitradas de la 29.ª Conferencia de Bases de Datos de Australasia, ADC 2018, celebrada en Gold Coast, QLD, Australia, en mayo de 2018. Los 23 artÃculos completos más 6 artÃculos breves presentados junto con 3 artÃculos de demostración fueron cuidadosamente revisados ​​y seleccionados entre 53 presentaciones. La Conferencia de Bases de Datos de Australasia es un foro internacional anual para compartir los últimos avances en investigación y aplicaciones novedosas de sistemas de bases de datos, aplicaciones basadas en datos y análisis de datos entre investigadores y profesionales de todo el mundo, particularmente Australia y Nueva Zelanda. Nota de contenido: Database and Applications -- Data mining and Applications -- Theories and Methodologies. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 29th Australasian Database Conference, ADC 2018, held in Gold Coast, QLD, Australia, in May 2018. The 23 full papers plus 6 short papers presented together with 3 demo papers were carefully reviewed and selected from 53 submissions. The Australasian Database Conference is an annual international forum for sharing the latest research advancements and novel applications of database systems, data-driven applications, and data analytics between researchers and practitioners from around the globe, particularly Australia and New Zealand. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] Databases Theory and Applications : 29th Australasian Database Conference, ADC 2018, Gold Coast, QLD, Australia, May 24-27, 2018, Proceedings [documento electrónico] / Wang, Junhu, ; Cong, Gao, ; Chen, Jinjun, ; Qi, Jianzhong, . - 1 ed. . - [s.l.] : Springer, 2018 . - XXV, 360 p. 149 ilustraciones.
ISBN : 978-3-319-92013-9
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
Idioma : Inglés (eng)
Palabras clave: Gestión de base de datos Procesamiento de datos Software de la aplicacion Inteligencia artificial Ciencias sociales Red de computadoras MinerÃa de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Aplicación informática en ciencias sociales y del comportamiento. Redes de comunicación informática Clasificación: 005.74 Ciencia de los computadores (Archivos de datos y bases de datos) Resumen: Este libro constituye las actas arbitradas de la 29.ª Conferencia de Bases de Datos de Australasia, ADC 2018, celebrada en Gold Coast, QLD, Australia, en mayo de 2018. Los 23 artÃculos completos más 6 artÃculos breves presentados junto con 3 artÃculos de demostración fueron cuidadosamente revisados ​​y seleccionados entre 53 presentaciones. La Conferencia de Bases de Datos de Australasia es un foro internacional anual para compartir los últimos avances en investigación y aplicaciones novedosas de sistemas de bases de datos, aplicaciones basadas en datos y análisis de datos entre investigadores y profesionales de todo el mundo, particularmente Australia y Nueva Zelanda. Nota de contenido: Database and Applications -- Data mining and Applications -- Theories and Methodologies. Tipo de medio : Computadora Summary : This book constitutes the refereed proceedings of the 29th Australasian Database Conference, ADC 2018, held in Gold Coast, QLD, Australia, in May 2018. The 23 full papers plus 6 short papers presented together with 3 demo papers were carefully reviewed and selected from 53 submissions. The Australasian Database Conference is an annual international forum for sharing the latest research advancements and novel applications of database systems, data-driven applications, and data analytics between researchers and practitioners from around the globe, particularly Australia and New Zealand. Enlace de acceso : https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...]
