Advances in Knowledge Discovery and Data Mining (häftad)
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
763
Utgivningsdatum
2015-04-14
Upplaga
2015 ed.
Förlag
Springer International Publishing AG
Medarbetare
Motoda, Hiroshi (red.)
Illustrationer
224 Illustrations, black and white; XXX, 763 p. 224 illus.
Volymtitel
Part I
Dimensioner
234 x 156 x 40 mm
Vikt
1094 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783319180373
Advances in Knowledge Discovery and Data Mining (häftad)

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

Häftad Engelska, 2015-04-14
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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.
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Innehållsförteckning

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 Heterogeneous 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.- Prediction 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 Hoelder 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