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Cao, Tru.
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Advances in knowledge discovery and data mining = 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015 : proceedings.. Part I /
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Advances in knowledge discovery and data mining/ edited by Tru Cao ... [et al.].
其他題名:
19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015 : proceedings.
其他題名:
PAKDD 2015
其他作者:
Cao, Tru.
出版者:
Cham :Springer International Publishing : : 2015.,
面頁冊數:
xxx, 763 p. :ill., digital ;24 cm.
內容註:
Social Networks and Social Media -- Maximizing Friend-Making Likelihood for Social Activity Organization -- What Is New in Our City? A Framework for Event Extraction Using Social Media Posts -- Link Prediction in Aligned Heterogeneous Networks -- Scale-Adaptive Group Optimization for Social Activity Planning -- Influence Maximization Across Partially Aligned Heterogenous Social Networks -- Multiple Factors-Aware Diffusion in Social Networks -- Understanding Community Effects on Information Diffusion -- On Burst Detection and Prediction in Retweeting Sequence -- Few Things About Idioms: Understanding Idioms and Its Users in the Twitter Online Social Network -- Retweeting Activity on Twitter: Signs of Reception -- Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network -- Classification -- Double Ramp Loss Based Reject Option Classifier -- Efficient Methods for Multi-label Classification -- A Coupled k-Nearest Neighbor Algorithm for Multi-label Classification -- Learning Topic-Oriented Word Embedding for Query Classification -- Reliable Early Classification on Multivariate Time Series with Numerical and Categorical Attributes -- Distributed Document Representation for Document Classification -- Prediciton of Emergency Events: A Multi-Task Multi-Label Learning Approach -- Nearest Neighbor Method Based on Local Distribution for Classification -- Immune Centroids Over-Sampling Method for Multi-Class Classification -- Optimizing Classifiers for Hypothetical Scenarios -- Repulsive-SVDD Classification -- Centroid-Means-Embedding: an Approach to Infusing Word Embeddings into Features for Text Classification -- Machine Learning -- Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning -- Multi-Task Metric Learning on Network Data -- A Bayesian Nonparametric Approach to Multilevel Regression -- Learning Conditional Latent Structures from Multiple Data Sources -- Collaborative Multi-view Learning with Active Discriminative Prior for Recommendation -- Online and Stochastic Universal Gradient Methods for Minimizing Regularized Holder Continuous Finite Sums in Machine Learning -- Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages -- Uncovering the Latent Structures of Crowd Labeling -- Use Correlation Coefficients in Gaussian Process to Train Stable ELM Models -- Local Adaptive and Incremental Gaussian Mixture for Online Density Estimation -- Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection -- A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization -- Applications -- On Damage Identification in Civil Structures Using Tensor Analysis -- Predicting Smartphone Adoption in Social Networks -- Discovering the Impact of Urban Traffic Interventions Using Contrast Mining on Vehicle Trajectory Data -- Locating Self-collection Points for Last-mile Logistics using Public Transport Data -- A Stochastic Framework for Solar Irradiance Forecasting Using Condition Random Field -- Online Prediction of Chess Match Result -- Learning of Performance Measures from Crowd-Sourced Data with Application to Ranking of Investments -- Hierarchical Dirichlet Process for Tracking Complex Topical Structure Evolution and its Application to Autism Research Literature -- Automated Detection for Probable Homologous Foodborne Disease Outbreaks -- Identifying Hesitant and Interested Customers for Targeted Social Marketing -- Activity-Partner Recommendation -- Iterative Use of Weighted Voronoi Diagrams to Improve Scalability in Recommender Systems -- Novel Methods and Algorithms Principal Sensitivity Analysis -- SocNL: Bayesian Label Propagation with Confidence -- An Incremental Local Distribution Network for Unsupervised Learning -- Trend-Based Citation Count Prediction for Research Articles -- Mining Text Enriched Heterogeneous Citation Networks -- Boosting via Approaching Optimal Margin Distribution -- o-HETM: An Online Hierarchical Entity Topic Model for News Streams -- Modeling User Interest and Community Interest in Microbloggings: An Integrated Approach -- Minimal Jumping Emerging Patterns: Computation and Practical Assessment -- Factorisation -- An Empirical Study of Personal Factors and Social Effects on Rating Prediction.
Contained By:
Springer eBooks
標題:
Data mining -
電子資源:
http://dx.doi.org/10.1007/978-3-319-18038-0
ISBN:
9783319180380 (electronic bk.)
Advances in knowledge discovery and data mining = 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015 : proceedings.. Part I /
Advances in knowledge discovery and data mining
19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015 : proceedings.Part I /[electronic resource] :PAKDD 2015edited by Tru Cao ... [et al.]. - Cham :Springer International Publishing :2015. - xxx, 763 p. :ill., digital ;24 cm. - Lecture notes in computer science,90770302-9743 ;. - Lecture notes in computer science ;5353..
Social Networks and Social Media -- Maximizing Friend-Making Likelihood for Social Activity Organization -- What Is New in Our City? A Framework for Event Extraction Using Social Media Posts -- Link Prediction in Aligned Heterogeneous Networks -- Scale-Adaptive Group Optimization for Social Activity Planning -- Influence Maximization Across Partially Aligned Heterogenous Social Networks -- Multiple Factors-Aware Diffusion in Social Networks -- Understanding Community Effects on Information Diffusion -- On Burst Detection and Prediction in Retweeting Sequence -- Few Things About Idioms: Understanding Idioms and Its Users in the Twitter Online Social Network -- Retweeting Activity on Twitter: Signs of Reception -- Resampling-Based Gap Analysis for Detecting Nodes with High Centrality on Large Social Network -- Classification -- Double Ramp Loss Based Reject Option Classifier -- Efficient Methods for Multi-label Classification -- A Coupled k-Nearest Neighbor Algorithm for Multi-label Classification -- Learning Topic-Oriented Word Embedding for Query Classification -- Reliable Early Classification on Multivariate Time Series with Numerical and Categorical Attributes -- Distributed Document Representation for Document Classification -- Prediciton of Emergency Events: A Multi-Task Multi-Label Learning Approach -- Nearest Neighbor Method Based on Local Distribution for Classification -- Immune Centroids Over-Sampling Method for Multi-Class Classification -- Optimizing Classifiers for Hypothetical Scenarios -- Repulsive-SVDD Classification -- Centroid-Means-Embedding: an Approach to Infusing Word Embeddings into Features for Text Classification -- Machine Learning -- Collaborating Differently on Different Topics: A Multi-Relational Approach to Multi-Task Learning -- Multi-Task Metric Learning on Network Data -- A Bayesian Nonparametric Approach to Multilevel Regression -- Learning Conditional Latent Structures from Multiple Data Sources -- Collaborative Multi-view Learning with Active Discriminative Prior for Recommendation -- Online and Stochastic Universal Gradient Methods for Minimizing Regularized Holder Continuous Finite Sums in Machine Learning -- Context-Aware Detection of Sneaky Vandalism on Wikipedia Across Multiple Languages -- Uncovering the Latent Structures of Crowd Labeling -- Use Correlation Coefficients in Gaussian Process to Train Stable ELM Models -- Local Adaptive and Incremental Gaussian Mixture for Online Density Estimation -- Latent Space Tracking from Heterogeneous Data with an Application for Anomaly Detection -- A Learning-Rate Schedule for Stochastic Gradient Methods to Matrix Factorization -- Applications -- On Damage Identification in Civil Structures Using Tensor Analysis -- Predicting Smartphone Adoption in Social Networks -- Discovering the Impact of Urban Traffic Interventions Using Contrast Mining on Vehicle Trajectory Data -- Locating Self-collection Points for Last-mile Logistics using Public Transport Data -- A Stochastic Framework for Solar Irradiance Forecasting Using Condition Random Field -- Online Prediction of Chess Match Result -- Learning of Performance Measures from Crowd-Sourced Data with Application to Ranking of Investments -- Hierarchical Dirichlet Process for Tracking Complex Topical Structure Evolution and its Application to Autism Research Literature -- Automated Detection for Probable Homologous Foodborne Disease Outbreaks -- Identifying Hesitant and Interested Customers for Targeted Social Marketing -- Activity-Partner Recommendation -- Iterative Use of Weighted Voronoi Diagrams to Improve Scalability in Recommender Systems -- Novel Methods and Algorithms Principal Sensitivity Analysis -- SocNL: Bayesian Label Propagation with Confidence -- An Incremental Local Distribution Network for Unsupervised Learning -- Trend-Based Citation Count Prediction for Research Articles -- Mining Text Enriched Heterogeneous Citation Networks -- Boosting via Approaching Optimal Margin Distribution -- o-HETM: An Online Hierarchical Entity Topic Model for News Streams -- Modeling User Interest and Community Interest in Microbloggings: An Integrated Approach -- Minimal Jumping Emerging Patterns: Computation and Practical Assessment -- Factorisation -- An Empirical Study of Personal Factors and Social Effects on Rating Prediction.
This two-volume set, LNAI 9077 + 9078, constitutes the refereed proceedings of the 19th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2015, held in Ho Chi Minh City, Vietnam, in May 2015. The proceedings contain 117 paper carefully reviewed and selected from 405 submissions. They have been organized in topical sections named: social networks and social media; classification; machine learning; applications; novel methods and algorithms; opinion mining and sentiment analysis; clustering; outlier and anomaly detection; mining uncertain and imprecise data; mining temporal and spatial data; feature extraction and selection; mining heterogeneous, high-dimensional, and sequential data; entity resolution and topic-modeling; itemset and high-performance data mining; and recommendations.
ISBN: 9783319180380 (electronic bk.)
Standard No.: 10.1007/978-3-319-18038-0doiSubjects--Topical Terms:
744342
Data mining
LC Class. No.: QA76.9.D343
Dewey Class. No.: 006.312
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