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Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xxxviii, 924 pages) : illustrations |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Application software Optical data processing Artificial Intelligence Information Systems and Communication Service Computer Applications Computing Milieux Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-030-47436-4 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Mining Sequential Data -- Mining Imbalanced Data -- Association -- Privacy and Security -- Supervised Learning -- Novel Algorithms -- Mining Multi-Media/Multi-Dimensional Data -- Application -- Mining Graph and Network Data -- Anomaly Detection and Analytics -- Mining Spatial, Temporal, Unstructured and Semi-Structured Data -- Sentiment Analysis -- Statistical/Graphical Model -- Multi-Source/Distributed/Parallel/Cloud Computing. |
| Record Nr. | UNINA-9910409665603321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part I / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part I / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xxxvii, 886 pages) : illustrations |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Application software Optical data processing Artificial Intelligence Information Systems and Communication Service Computer Applications Computing Milieux Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-030-47426-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Recommender Systems -- Classification -- Clustering -- Mining Social Networks -- Representation Learning and Embedding -- Mining Behavioral Data -- Deep Learning -- Feature Extraction and Selection -- Human, Domain, Organizational and Social Factors in Data Mining. |
| Record Nr. | UNINA-9910409665503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part I / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part I / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xxxvii, 886 pages) : illustrations |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Application software Optical data processing Artificial Intelligence Information Systems and Communication Service Computer Applications Computing Milieux Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-030-47426-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Recommender Systems -- Classification -- Clustering -- Mining Social Networks -- Representation Learning and Embedding -- Mining Behavioral Data -- Deep Learning -- Feature Extraction and Selection -- Human, Domain, Organizational and Social Factors in Data Mining. |
| Record Nr. | UNISA-996418314003316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 24th Pacific-Asia Conference, PAKDD 2020, Singapore, May 11–14, 2020, Proceedings, Part II / / edited by Hady W. Lauw, Raymond Chi-Wing Wong, Alexandros Ntoulas, Ee-Peng Lim, See-Kiong Ng, Sinno Jialin Pan |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xxxviii, 924 pages) : illustrations |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Computers Application software Optical data processing Artificial Intelligence Information Systems and Communication Service Computer Applications Computing Milieux Computer Imaging, Vision, Pattern Recognition and Graphics |
| ISBN | 3-030-47436-4 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Mining Sequential Data -- Mining Imbalanced Data -- Association -- Privacy and Security -- Supervised Learning -- Novel Algorithms -- Mining Multi-Media/Multi-Dimensional Data -- Application -- Mining Graph and Network Data -- Anomaly Detection and Analytics -- Mining Spatial, Temporal, Unstructured and Semi-Structured Data -- Sentiment Analysis -- Statistical/Graphical Model -- Multi-Source/Distributed/Parallel/Cloud Computing. |
| Record Nr. | UNISA-996418314603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXX, 763 p. 224 illus.) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Information storage and retrieval Data Mining and Knowledge Discovery Artificial Intelligence Information Storage and Retrieval |
| ISBN | 3-319-18038-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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 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. |
| Record Nr. | UNINA-9910484174703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXIX, 773 p. 237 illus.) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Information storage and retrieval Data Mining and Knowledge Discovery Artificial Intelligence Information Storage and Retrieval |
| ISBN | 3-319-18032-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Opinion Mining and Sentiment Analysis -- Emotion Cause Detection for Chinese Micro-Blogs Based on ECOCC Model -- Parallel Recursive Deep Model for Sentiment Analysis -- Sentiment Analysis in Transcribed Utterances -- Rating Entities and Aspects Using a Hierarchical Model -- Sentiment Analysis on Microblogging by Integrating Text and Image Features -- TSum4act: A Framework for Retrieving and Summarizing Actionable Tweets during a Disaster for Reaction -- Clustering -- Evolving Chinese Restaurant Processes for Modeling Evolutionary Traces in Temporal Data -- Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints -- Spectral Clustering for Large-Scale Social Networks via a Pre-Coarsening Sampling Based Nyström Method -- pcStream: A Stream Clustering Algorithm for Dynamically Detecting and Managing Temporal Contexts -- Clustering Over Data Streams Based on Growing Neural Gas -- Computing and Mining ClustCube Cubes Efficiently -- Outlier and Anomaly Detection Contextual Anomaly Detection Using Log-Linear Tensor Factorization -- A Semi-Supervised Framework for Social Spammer Detection -- Fast One-Class Support Vector Machine for Novelty Detection -- ND-SYNC: Detecting Synchronized Fraud Activities -- An Embedding Scheme for Detecting Anomalous Block Structured Graphs -- A Core-Attach Based Method for Identifying Protein Complexes in Dynamic PPI Networks -- Mining Uncertain and Imprecise Data Mining Uncertain Sequential Patterns in Iterative MapReduce -- Quality Control for Crowdsourced POI Collection -- Towards Efficient Sequential Pattern Mining in Temporal Uncertain Databases -- Preference-Based Top-k Representative Skyline Queries on Uncertain Databases -- Cluster Sequence Mining: Causal Inference with Time and Space Proximity under Uncertainty -- Achieving Accuracy Guarantee for Answering Batch Queries with Differential Privacy -- Mining Temporal and Spatial Data Automated Classification of Passing in Football -- Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records -- Predicting Next Locations with Object Clustering and Trajectory Clustering -- A Plane Moving Average Algorithm for Short-Term Traffic Flow Prediction -- Recommending Profitable Taxi Travel Routes Based on Big Taxi Trajectories Data -- Semi Supervised Adaptive Framework for Classifying Evolving Data Stream -- Feature Extraction and Selection Cost-Sensitive Feature Selection on Heterogeneous Data -- A Feature Extraction Method for Multivariate Time Series Classification Using Temporal Patterns -- Scalable Outlying-Inlying Aspects Discovery via Feature Ranking -- A DC Programming Approach for Sparse Optimal Scoring -- Graph Based Relational Features for Collective Classification -- A New Feature Sampling Method in Random Forests for Predicting High-Dimensional Data -- Mining Heterogeneous, High Dimensional, and Sequential Data Seamlessly Integrating Effective Links with Attributes for Networked Data Classification -- Clustering on Multi-source Incomplete Data via Tensor Modeling and Factorization -- Locally Optimized Hashing for Nearest Neighbor Search -- Do-Rank: DCG Optimization for Learning-to-Rank in Tag-Based Item Recommendation Systems -- Efficient Discovery of Recurrent Routine Behaviours in Smart Meter Time Series by Growing Subsequences -- Convolutional Nonlinear Neighbourhood Components Analysis for Time Series Classification -- Entity Resolution and Topic Modelling Clustering-Based Scalable Indexing for Multi-party Privacy-Preserving Record Linkage -- Efficient Interactive Training Selection for Large-Scale Entity Resolution -- Unsupervised Blocking Key Selection for Real-Time Entity Resolution -- Incorporating Probabilistic Knowledge into Topic Models -- Learning Focused Hierarchical Topic Models with Semi-Supervision in Microblogs -- Predicting Future Links Between Disjoint Research Areas Using Heterogeneous Bibliographic Information Network -- Itemset and High Performance Data Mining CPT+: Decreasing the Time/Space Complexity of the Compact Prediction Tree -- Mining Association Rules in Graphs Based on Frequent Cohesive Itemsets -- Mining High Utility Itemsets in Big Data -- Decomposition Based SAT Encodings for Itemset Mining Problems -- A Comparative Study on Parallel LDA Algorithms in MapReduce Framework -- Distributed Newton Methods for Regularized Logistic Regression -- Recommendation -- Coupled Matrix Factorization Within Non-IID Context -- Complementary Usage of Tips and Reviews for Location Recommendation in Yelp -- Coupling Multiple Views of Relations for Recommendation -- Pairwise One Class Recommendation Algorithm -- RIT: Enhancing Recommendation with Inferred Trust. |
| Record Nr. | UNINA-9910484071703321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part I / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXX, 763 p. 224 illus.) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Information storage and retrieval Data Mining and Knowledge Discovery Artificial Intelligence Information Storage and Retrieval |
| ISBN | 3-319-18038-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 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 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. |
| Record Nr. | UNISA-996207294203316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda
| Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 19th Pacific-Asia Conference, PAKDD 2015, Ho Chi Minh City, Vietnam, May 19-22, 2015, Proceedings, Part II / / edited by Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda |
| Edizione | [1st ed. 2015.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
| Descrizione fisica | 1 online resource (XXIX, 773 p. 237 illus.) |
| Disciplina | 006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Information storage and retrieval Data Mining and Knowledge Discovery Artificial Intelligence Information Storage and Retrieval |
| ISBN | 3-319-18032-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Opinion Mining and Sentiment Analysis -- Emotion Cause Detection for Chinese Micro-Blogs Based on ECOCC Model -- Parallel Recursive Deep Model for Sentiment Analysis -- Sentiment Analysis in Transcribed Utterances -- Rating Entities and Aspects Using a Hierarchical Model -- Sentiment Analysis on Microblogging by Integrating Text and Image Features -- TSum4act: A Framework for Retrieving and Summarizing Actionable Tweets during a Disaster for Reaction -- Clustering -- Evolving Chinese Restaurant Processes for Modeling Evolutionary Traces in Temporal Data -- Small-Variance Asymptotics for Bayesian Nonparametric Models with Constraints -- Spectral Clustering for Large-Scale Social Networks via a Pre-Coarsening Sampling Based Nyström Method -- pcStream: A Stream Clustering Algorithm for Dynamically Detecting and Managing Temporal Contexts -- Clustering Over Data Streams Based on Growing Neural Gas -- Computing and Mining ClustCube Cubes Efficiently -- Outlier and Anomaly Detection Contextual Anomaly Detection Using Log-Linear Tensor Factorization -- A Semi-Supervised Framework for Social Spammer Detection -- Fast One-Class Support Vector Machine for Novelty Detection -- ND-SYNC: Detecting Synchronized Fraud Activities -- An Embedding Scheme for Detecting Anomalous Block Structured Graphs -- A Core-Attach Based Method for Identifying Protein Complexes in Dynamic PPI Networks -- Mining Uncertain and Imprecise Data Mining Uncertain Sequential Patterns in Iterative MapReduce -- Quality Control for Crowdsourced POI Collection -- Towards Efficient Sequential Pattern Mining in Temporal Uncertain Databases -- Preference-Based Top-k Representative Skyline Queries on Uncertain Databases -- Cluster Sequence Mining: Causal Inference with Time and Space Proximity under Uncertainty -- Achieving Accuracy Guarantee for Answering Batch Queries with Differential Privacy -- Mining Temporal and Spatial Data Automated Classification of Passing in Football -- Stabilizing Sparse Cox Model Using Statistic and Semantic Structures in Electronic Medical Records -- Predicting Next Locations with Object Clustering and Trajectory Clustering -- A Plane Moving Average Algorithm for Short-Term Traffic Flow Prediction -- Recommending Profitable Taxi Travel Routes Based on Big Taxi Trajectories Data -- Semi Supervised Adaptive Framework for Classifying Evolving Data Stream -- Feature Extraction and Selection Cost-Sensitive Feature Selection on Heterogeneous Data -- A Feature Extraction Method for Multivariate Time Series Classification Using Temporal Patterns -- Scalable Outlying-Inlying Aspects Discovery via Feature Ranking -- A DC Programming Approach for Sparse Optimal Scoring -- Graph Based Relational Features for Collective Classification -- A New Feature Sampling Method in Random Forests for Predicting High-Dimensional Data -- Mining Heterogeneous, High Dimensional, and Sequential Data Seamlessly Integrating Effective Links with Attributes for Networked Data Classification -- Clustering on Multi-source Incomplete Data via Tensor Modeling and Factorization -- Locally Optimized Hashing for Nearest Neighbor Search -- Do-Rank: DCG Optimization for Learning-to-Rank in Tag-Based Item Recommendation Systems -- Efficient Discovery of Recurrent Routine Behaviours in Smart Meter Time Series by Growing Subsequences -- Convolutional Nonlinear Neighbourhood Components Analysis for Time Series Classification -- Entity Resolution and Topic Modelling Clustering-Based Scalable Indexing for Multi-party Privacy-Preserving Record Linkage -- Efficient Interactive Training Selection for Large-Scale Entity Resolution -- Unsupervised Blocking Key Selection for Real-Time Entity Resolution -- Incorporating Probabilistic Knowledge into Topic Models -- Learning Focused Hierarchical Topic Models with Semi-Supervision in Microblogs -- Predicting Future Links Between Disjoint Research Areas Using Heterogeneous Bibliographic Information Network -- Itemset and High Performance Data Mining CPT+: Decreasing the Time/Space Complexity of the Compact Prediction Tree -- Mining Association Rules in Graphs Based on Frequent Cohesive Itemsets -- Mining High Utility Itemsets in Big Data -- Decomposition Based SAT Encodings for Itemset Mining Problems -- A Comparative Study on Parallel LDA Algorithms in MapReduce Framework -- Distributed Newton Methods for Regularized Logistic Regression -- Recommendation -- Coupled Matrix Factorization Within Non-IID Context -- Complementary Usage of Tips and Reviews for Location Recommendation in Yelp -- Coupling Multiple Views of Relations for Recommendation -- Pairwise One Class Recommendation Algorithm -- RIT: Enhancing Recommendation with Inferred Trust. |
| Record Nr. | UNISA-996200028603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Computational trust models and machine learning / / edited by Xin Liu, EPFL, Lausanne, Switzerland, Anwitaman Datta, Nanyang Technological University, Singapore, Ee-Peng Lim, Singapore Management University
| Computational trust models and machine learning / / edited by Xin Liu, EPFL, Lausanne, Switzerland, Anwitaman Datta, Nanyang Technological University, Singapore, Ee-Peng Lim, Singapore Management University |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton : , : Taylor & Francis, , [2015] |
| Descrizione fisica | 1 online resource (227 p.) |
| Disciplina | 006.31 |
| Collana | Chapman & Hall/CRC machine learning & pattern recognition series |
| Soggetto topico |
Computational intelligence
Machine learning Truthfulness and falsehood - Mathematical models |
| ISBN |
0-429-15948-X
1-4822-2667-7 |
| Classificazione | COM037000COM051240TEC008000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Series Page; Dedication; Contents; List of Figures; Preface; About the Editors; Contributors; Chapter 1: Introduction; Chapter 2: Trust in Online Communities; Chapter 3: Judging the Veracity of Claims and Reliability of Sources with Fact-Finders; Chapter 4: Web Credibility Assessment; Chapter 5: Trust-Aware Recommender Systems; Chapter 6: Biases in Trust-Based Systems; Bibliography; Back Cover |
| Record Nr. | UNINA-9910787962603321 |
| Boca Raton : , : Taylor & Francis, , [2015] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Computational trust models and machine learning / / edited by Xin Liu, EPFL, Lausanne, Switzerland, Anwitaman Datta, Nanyang Technological University, Singapore, Ee-Peng Lim, Singapore Management University
| Computational trust models and machine learning / / edited by Xin Liu, EPFL, Lausanne, Switzerland, Anwitaman Datta, Nanyang Technological University, Singapore, Ee-Peng Lim, Singapore Management University |
| Edizione | [1st edition] |
| Pubbl/distr/stampa | Boca Raton : , : Taylor & Francis, , [2015] |
| Descrizione fisica | 1 online resource (227 p.) |
| Disciplina | 006.31 |
| Collana | Chapman & Hall/CRC machine learning & pattern recognition series |
| Soggetto topico |
Computational intelligence
Machine learning Truthfulness and falsehood - Mathematical models |
| ISBN |
0-429-15948-X
1-4822-2667-7 |
| Classificazione | COM037000COM051240TEC008000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Front Cover; Series Page; Dedication; Contents; List of Figures; Preface; About the Editors; Contributors; Chapter 1: Introduction; Chapter 2: Trust in Online Communities; Chapter 3: Judging the Veracity of Claims and Reliability of Sources with Fact-Finders; Chapter 4: Web Credibility Assessment; Chapter 5: Trust-Aware Recommender Systems; Chapter 6: Biases in Trust-Based Systems; Bibliography; Back Cover |
| Record Nr. | UNINA-9910800184703321 |
| Boca Raton : , : Taylor & Francis, , [2015] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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