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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 - Tru Cao
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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 - Taschenbuch

2015, ISBN: 3319180371

[EAN: 9783319180373], Neubuch, [SC: 0.0], [PU: Springer International Publishing], CLASSIFICATION; CLUSTERING; COLLABORATIVECOMPUTING; DATASTREAMS; FACTORIZATIONMETHODS; INFORMATIONRETRIE… Mehr…

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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 - Cao, Tru (Herausgeber); Lim, Ee-Peng (Herausgeber); Motoda, Hiroshi (Herausgeber); Ho, Tu-Bao (Herausgeber); Cheung, David (Herausgeber); Zhou, Zhi-Hua (Herausgeber)
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Cao, Tru (Herausgeber); Lim, Ee-Peng (Herausgeber); Motoda, Hiroshi (Herausgeber); Ho, Tu-Bao (Herausgeber); Cheung, David (Herausgeber); Zhou, Zhi-Hua (Herausgeber):

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2015, ISBN: 3319180371

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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 - Cao, Tru (Herausgeber); Lim, Ee-Peng (Herausgeber); Motoda, Hiroshi (Herausgeber); Ho, Tu-Bao (Herausgeber); Cheung, David (Herausgeber); Zhou, Zhi-Hua (Herausgeber)
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Cao, Tru (Herausgeber); Lim, Ee-Peng (Herausgeber); Motoda, Hiroshi (Herausgeber); Ho, Tu-Bao (Herausgeber); Cheung, David (Herausgeber); Zhou, Zhi-Hua (Herausgeber):
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 - neues Buch

2015

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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 - Cao, Tru (Herausgeber); Lim, Ee-Peng (Herausgeber); Motoda, Hiroshi (Herausgeber); Ho, Tu-Bao (Herausgeber); Cheung, David (Herausgeber); Zhou, Zhi-Hua (Herausgeber)
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Cao, Tru (Herausgeber); Lim, Ee-Peng (Herausgeber); Motoda, Hiroshi (Herausgeber); Ho, Tu-Bao (Herausgeber); Cheung, David (Herausgeber); Zhou, Zhi-Hua (Herausgeber):
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 - neues Buch

2015, ISBN: 3319180371

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Advances in Knowledge Discovery and Data Mining - Taschenbuch

2015, ISBN: 9783319180373

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Advances in Knowledge Discovery and Data Mining
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Titel:
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9783319180373

Detailangaben zum Buch - Advances in Knowledge Discovery and Data Mining


EAN (ISBN-13): 9783319180373
ISBN (ISBN-10): 3319180371
Gebundene Ausgabe
Taschenbuch
Erscheinungsjahr: 2015
Herausgeber: Springer International Publishing

Buch in der Datenbank seit 2015-03-24T09:21:21+01:00 (Zurich)
Detailseite zuletzt geändert am 2023-12-18T17:32:22+01:00 (Zurich)
ISBN/EAN: 9783319180373

ISBN - alternative Schreibweisen:
3-319-18037-1, 978-3-319-18037-3
Alternative Schreibweisen und verwandte Suchbegriffe:
Autor des Buches: peng, lim, hua, zhou, cheung
Titel des Buches: data mining, chi minh, knowledge discovery, pacific discovery

Daten vom Verlag:

Autor/in: Tru Cao; Ee-Peng Lim; Zhi-Hua Zhou; Tu-Bao Ho; David Cheung; Hiroshi Motoda
Titel: Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence; 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
Verlag: Springer; Springer International Publishing
763 Seiten
Erscheinungsjahr: 2015-04-22
Cham; CH
Gedruckt / Hergestellt in Niederlande.
Sprache: Englisch
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
POD
XXX, 763 p. 224 illus.

BC; Hardcover, Softcover / Informatik, EDV/Informatik; Data Mining; Verstehen; classification; clustering; collaborative computing; data streams; factorization methods; information retrieval; kernel methods; learning paradigms; machine learning; machine learning algorithms; probabilistic reasoning; recommender systems; retrieval tasks and goals; sentiment analysis; social computing; social networks; supervised learning; temporal data; uncertainty; unsupervised learning; Data Mining and Knowledge Discovery; Artificial Intelligence; Information Storage and Retrieval; Wissensbasierte Systeme, Expertensysteme; Künstliche Intelligenz; Informationsrückgewinnung, Information Retrieval; Data Warehousing; EA

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 Hölder 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 TopicModel 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.

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