| Título : |
European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III |
| Tipo de documento: |
documento electrónico |
| Autores: |
Altun, Yasemin, ; Das, Kamalika, ; Mielikäinen, Taneli, ; Malerba, Donato, ; Stefanowski, Jerzy, ; Read, Jesse, ; Žitnik, Marinka, ; Ceci, Michelangelo, ; Džeroski, Sašo, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2017 |
| Número de páginas: |
XXXV, 448 p. 144 ilustraciones |
| ISBN/ISSN/DL: |
978-3-319-71273-4 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Procesamiento de datos Inteligencia artificial Visión por computador Software de la aplicacion Protección de datos Ordenadores Minería de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Seguridad de datos e información Entornos informáticos |
| Índice Dewey: |
6.312 |
| Resumen: |
Las actas de tres volúmenes LNAI 10534 – 10536 constituyen las actas arbitradas de la Conferencia Europea sobre Aprendizaje Automático y Descubrimiento de Conocimiento en Bases de Datos, ECML PKDD 2017, celebrada en Skopje, Macedonia, en septiembre de 2017. El total de 101 artículos regulares presentados en la parte I y la parte II fue cuidadosamente revisada y seleccionada entre 364 presentaciones; Hay 47 artículos en la sección de demostración, néctar y ciencia de datos aplicada. Las contribuciones se organizaron en secciones temáticas denominadas de la siguiente manera: Parte I: detección de anomalías; visión por computador; conjuntos y metaaprendizaje; selección y extracción de características; métodos del núcleo; aprendizaje y optimización, factorización matricial y tensorial; redes y gráficos; Redes neuronales y aprendizaje profundo. Parte II: minería de patrones y secuencias; privacidad y seguridad; modelos y métodos probabilísticos; recomendación; regresión; aprendizaje reforzado; descubrimiento de subgrupos; series de tiempo y flujos; transferencia y aprendizaje multitarea; Aprendizaje no supervisado y semisupervisado. Parte III: pista de ciencia de datos aplicada; pista de néctar; y pista de demostración. |
| Nota de contenido: |
Applied Data Science track -- A Novel Framework for Online Sales Burst Prediction -- Analyzing Granger causality in climate data with time series classification methods -- Automatic Detection and Recognition of Individuals in Patterned Species -- Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting -- CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining -- DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters -- Disjoint-Support Factors and Seasonality Estimation in E-Commerce -- Event Detection and Summarization using Phrase Networks: PhraseNet -- Generalising Random Forest Parameter Optimisation to Include Stability and Cost -- Have It Both Ways - from A/B Testing to A&B Testing with Exceptional Model Mining -- Koopman spectral kernels for comparing complex dynamics: Application to multiagent sport plays -- Modeling the Temporal Nature of Human Behavior for Demographics Prediction -- MRNet-Product2Vec: A Multi-task Recurrent Neural Network for Product Embeddings -- Optimal client recommendation for market makers in illiquid financial products -- Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center -- Probabilistic Inference of Twitter Users' Age based on What They Follow -- Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects -- RSSI Based Supervised Learning for Uncooperative Direction-Finding -- Sequential Keystroke Behavioral Biometrics for User Identification via Multi-view Deep Learning -- Session-Based Fraud Detection in Online E-Commerce Transactions Using Recurrent Neural Networks -- SINAS: Suspect Investigation Using Offenders' Activity Space -- Stance Classification of Tweets using Skip Char NGrams -- Structural Semantic Models for Automatic Analysis of Urban Areas -- Taking it for a Test Drive: A Hybrid Spatio-temporal Model for Wildlife Poaching Prediction Evaluated through a Controlled Field Test -- Unsupervised signature extraction from forensic logs -- Urban Water Flow and Water Level Prediction based on Deep Learning -- Using Machine Learning for Labour Market Intelligence -- Nectar track -- Activity-Driven Influence Maximization in Social Networks -- An AI Planning System for Data Cleaning -- Comparing hypotheses on sequential behavior: A Bayesian approach and its applications -- Data-driven Approaches for Smart Parking -- Image representation, annotation and retrieval with predictive clustering trees -- Music Generation Using Bayesian Networks -- Phenotype Inference from Text and Genomic Data -- Process-based Modeling and Design of Dynamical Systems -- QuickScorer: Efficient Traversal of Large Ensembles of Decision Trees -- Recent Advances in Kernel-Based Graph Classification -- Demo track -- ASK-the-Expert: Active learning based knowledge discovery using the expert -- Delve: A Data set Retrieval and Document Analysis System -- Framework for Exploring and Understanding Multivariate Correlations -- Lit@EVE: Explainable Recommendation based on Wikipedia Concept Vectors -- Monitoring Physical Activity and Mental Stress using Wrist-worn Device and a Smartphone -- Tetrahedron: Barycentric Measure Visualizer -- TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting -- TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory -- TrAnET: Tracking and Analyzing the Evolution of Topics in Information Networks -- WHODID: Web-based interface for Human-assisted factory Operations in fault Detection, Identification and Diagnosis. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18–22, 2017, Proceedings, Part III [documento electrónico] / Altun, Yasemin, ; Das, Kamalika, ; Mielikäinen, Taneli, ; Malerba, Donato, ; Stefanowski, Jerzy, ; Read, Jesse, ; Žitnik, Marinka, ; Ceci, Michelangelo, ; Džeroski, Sašo, . - 1 ed. . - [s.l.] : Springer, 2017 . - XXXV, 448 p. 144 ilustraciones. ISBN : 978-3-319-71273-4 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Procesamiento de datos Inteligencia artificial Visión por computador Software de la aplicacion Protección de datos Ordenadores Minería de datos y descubrimiento de conocimientos Aplicaciones informáticas y de sistemas de información Seguridad de datos e información Entornos informáticos |
| Índice Dewey: |
6.312 |
| Resumen: |
Las actas de tres volúmenes LNAI 10534 – 10536 constituyen las actas arbitradas de la Conferencia Europea sobre Aprendizaje Automático y Descubrimiento de Conocimiento en Bases de Datos, ECML PKDD 2017, celebrada en Skopje, Macedonia, en septiembre de 2017. El total de 101 artículos regulares presentados en la parte I y la parte II fue cuidadosamente revisada y seleccionada entre 364 presentaciones; Hay 47 artículos en la sección de demostración, néctar y ciencia de datos aplicada. Las contribuciones se organizaron en secciones temáticas denominadas de la siguiente manera: Parte I: detección de anomalías; visión por computador; conjuntos y metaaprendizaje; selección y extracción de características; métodos del núcleo; aprendizaje y optimización, factorización matricial y tensorial; redes y gráficos; Redes neuronales y aprendizaje profundo. Parte II: minería de patrones y secuencias; privacidad y seguridad; modelos y métodos probabilísticos; recomendación; regresión; aprendizaje reforzado; descubrimiento de subgrupos; series de tiempo y flujos; transferencia y aprendizaje multitarea; Aprendizaje no supervisado y semisupervisado. Parte III: pista de ciencia de datos aplicada; pista de néctar; y pista de demostración. |
| Nota de contenido: |
Applied Data Science track -- A Novel Framework for Online Sales Burst Prediction -- Analyzing Granger causality in climate data with time series classification methods -- Automatic Detection and Recognition of Individuals in Patterned Species -- Boosting Based Multiple Kernel Learning and Transfer Regression for Electricity Load Forecasting -- CREST - Risk Prediction for Clostridium Difficile Infection Using Multimodal Data Mining -- DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters -- Disjoint-Support Factors and Seasonality Estimation in E-Commerce -- Event Detection and Summarization using Phrase Networks: PhraseNet -- Generalising Random Forest Parameter Optimisation to Include Stability and Cost -- Have It Both Ways - from A/B Testing to A&B Testing with Exceptional Model Mining -- Koopman spectral kernels for comparing complex dynamics: Application to multiagent sport plays -- Modeling the Temporal Nature of Human Behavior for Demographics Prediction -- MRNet-Product2Vec: A Multi-task Recurrent Neural Network for Product Embeddings -- Optimal client recommendation for market makers in illiquid financial products -- Predicting Self-reported Customer Satisfaction of Interactions with a Corporate Call Center -- Probabilistic Inference of Twitter Users' Age based on What They Follow -- Quantifying Heterogeneous Causal Treatment Effects in World Bank Development Finance Projects -- RSSI Based Supervised Learning for Uncooperative Direction-Finding -- Sequential Keystroke Behavioral Biometrics for User Identification via Multi-view Deep Learning -- Session-Based Fraud Detection in Online E-Commerce Transactions Using Recurrent Neural Networks -- SINAS: Suspect Investigation Using Offenders' Activity Space -- Stance Classification of Tweets using Skip Char NGrams -- Structural Semantic Models for Automatic Analysis of Urban Areas -- Taking it for a Test Drive: A Hybrid Spatio-temporal Model for Wildlife Poaching Prediction Evaluated through a Controlled Field Test -- Unsupervised signature extraction from forensic logs -- Urban Water Flow and Water Level Prediction based on Deep Learning -- Using Machine Learning for Labour Market Intelligence -- Nectar track -- Activity-Driven Influence Maximization in Social Networks -- An AI Planning System for Data Cleaning -- Comparing hypotheses on sequential behavior: A Bayesian approach and its applications -- Data-driven Approaches for Smart Parking -- Image representation, annotation and retrieval with predictive clustering trees -- Music Generation Using Bayesian Networks -- Phenotype Inference from Text and Genomic Data -- Process-based Modeling and Design of Dynamical Systems -- QuickScorer: Efficient Traversal of Large Ensembles of Decision Trees -- Recent Advances in Kernel-Based Graph Classification -- Demo track -- ASK-the-Expert: Active learning based knowledge discovery using the expert -- Delve: A Data set Retrieval and Document Analysis System -- Framework for Exploring and Understanding Multivariate Correlations -- Lit@EVE: Explainable Recommendation based on Wikipedia Concept Vectors -- Monitoring Physical Activity and Mental Stress using Wrist-worn Device and a Smartphone -- Tetrahedron: Barycentric Measure Visualizer -- TF Boosted Trees: A scalable TensorFlow based framework for gradient boosting -- TrajViz: A Tool for Visualizing Patterns and Anomalies in Trajectory -- TrAnET: Tracking and Analyzing the Evolution of Topics in Information Networks -- WHODID: Web-based interface for Human-assisted factory Operations in fault Detection, Identification and Diagnosis. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
|  |
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