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Advanced Data Mining and Applications [[electronic resource] ] : 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings / / edited by Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li, Aixin Sun
Advanced Data Mining and Applications [[electronic resource] ] : 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings / / edited by Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li, Aixin Sun
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XVII, 881 p. 264 illus.)
Disciplina 006.312
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Data mining
Information storage and retrieval
Application software
Natural language processing (Computer science)
Computer communication systems
Artificial Intelligence
Data Mining and Knowledge Discovery
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
Natural Language Processing (NLP)
Computer Communication Networks
ISBN 3-319-69179-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Database and Distributed Machine Learning -- Querying and Mining Strings Made Easy Distributed Training Large-Scale Deep Architectures -- Fault Detection and Localization in Distributed Systems using Recurrent Convolutional Neural Networks -- Discovering Group Skylines with Constraints by Early Candidate Pruning -- Comparing MapReduce-Based k-NN Similarity Joins On Hadoop For High-dimensional Data -- A Higher-Fidelity Frugal Quantile Estimator -- Recommender System -- Fair Recommendations Through Diversity Promotion -- A Hierarchical Bayesian Factorization Model for Implicit and Explicit Feedback Data -- Empirical Analysis of Factors Influencing Twitter Hashtag Recommendation on Detected Communities -- Group Recommender Model Based on Preference Interaction -- Identification of Grey Sheep Users By Histogram Intersection In Recommender Systems -- Social Network and Social Media -- A Feature-based Approach for the Redefined Link Prediction Problem in Signed Networks -- From Mutual Friends to Overlapping Community Detection: A Non-negative Matrix Factorization Approach -- Calling for Response: Automatically Distinguishing Situation-aware Tweets During Crises -- Efficient Revenue Maximization for Viral Marketing in Social Networks -- Generating Life Course Trajectory Sequences with Recurrent Neural Networks and Application to Early Detection on Social Disadvantage -- FRISK: A Multilingual Approach to Find twitteR InterestS via wiKipedia -- A Solution to Tweet-Based User Identification across Online Social Networks -- Machine Learning -- Supervised Feature Selection Algorithm Based on Low-Rank and Manifold Learning -- Mixed Membership Sparse Gaussian Conditional Random Fields -- Effects of Dynamic Subspacing in Random Forest -- Diversity and Locality in Multi-Component, Multi-Layer Predictive Systems: A Mutual Information Based Approach -- Hybrid Subspace Mixture Models For Prediction and Anomaly Detection in High Dimensions -- Classification and Clustering Methods --  StruClus: Scalable Structural Graph Set Clustering with Representative Sampling -- Employing Hierarchical Clustering and Reinforcement Learning for Attribute-based Zero-Shot Classification -- Environmental Sound Recognition using Masked Conditional Neural Networks -- Analyzing Performance of Classification Techniques in Detecting Epileptic Seizure -- A Framework for Clustering and Dynamic Maintenance of XML Documents -- Language-independent Twitter Classification using Character-based Convolutional Networks -- Behavior Modeling and User Profiling -- Modeling Check-in Behavior with Geographical Neighborhood Influence of Venues -- An empirical study on collective online behaviors of extremist supporters. -Your Moves, Your Device: Establishing Behavior Profiles using Tensors -- An Approach for Identifying Author Profiles of Blogs -- Generating Topics of Interests for Research Communities -- An Evolutionary Approach for Learning Conditional Preference Network from Inconsistent Examples -- Bioinformatic and Medical Data Analysis -- Predicting Clinical Outcomes of Alzheimer's Disease from Complex Brain Networks -- Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties -- Multiclass Lung Cancer Diagnosis by Gene Expression Programming and Microarray Datasets -- Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers -- Spatio-temporal Data -- People-Centric Mobile Crowdsensing Platform for Urban Design -- Long-Term User Location Prediction Using Deep Learning and Periodic Pattern Mining -- An Intelligent Weighted Fuzzy Time Series Model Based on A Sine-Cosine Adaptive Human Learning Optimization Algorithm and Its Application to Financial Markets Forecasting -- Mobile Robot Scheduling with Multiple Trips and Time Windows -- Natural Language Processing and Text Mining -- Feature Analysis for Duplicate Detection in Programming QA Communities -- A Joint Human/Machine Process for Coding Events and Conflict Drivers -- Quality Prediction of Newly Proposed Questions in CQA by Leveraging Weakly Supervised Learning -- Improving Chinese Sentiment Analysis via Segmentation-based Representation Using Parallel CNN -- Entity Recognition by Distant Supervision with Soft List Constraint -- Structured Sentiment Analysis -- Data Mining Applications -- Improving Real-Time Bidding Using a Constrained Markov Decision Process -- PowerLSTM: Power Demand Forecasting Using Long Short-Term Memory Neural Network -- Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments -- Color-sketch simulator: a guide for color-based visual known-item search -- Applications -- Making Use of External Company Data to Improve the Classification of Bank Transactions -- Mining Load Profile Patterns for Australian Electricity Consumers -- STA: a Spatio-temporal Thematic Analytics Framework for Urban Ground Sensing -- Privacy and Utility Preservation for Location Data Using Stay Region Analysis -- Location-aware Human Activity Recognition -- Demos -- SWYSWYK: a new Sharing Paradigm for the Personal Cloud -- Tools and Infrastructure for Supporting Enterprise Knowledge Graphs -- An Interactive Web-based Toolset for Knowledge Discovery from Short Text Log Data -- Carbon: Forecasting Civil Unrest Events by Monitoring News and Social Media -- A system for Querying and Analyzing Urban Regions -- Detect tracking behavior among trajectory data.
Record Nr. UNINA-9910484704803321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced Data Mining and Applications [[electronic resource] ] : 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings / / edited by Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li, Aixin Sun
Advanced Data Mining and Applications [[electronic resource] ] : 13th International Conference, ADMA 2017, Singapore, November 5–6, 2017, Proceedings / / edited by Gao Cong, Wen-Chih Peng, Wei Emma Zhang, Chengliang Li, Aixin Sun
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XVII, 881 p. 264 illus.)
Disciplina 006.312
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Data mining
Information storage and retrieval
Application software
Natural language processing (Computer science)
Computer communication systems
Artificial Intelligence
Data Mining and Knowledge Discovery
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
Natural Language Processing (NLP)
Computer Communication Networks
ISBN 3-319-69179-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Database and Distributed Machine Learning -- Querying and Mining Strings Made Easy Distributed Training Large-Scale Deep Architectures -- Fault Detection and Localization in Distributed Systems using Recurrent Convolutional Neural Networks -- Discovering Group Skylines with Constraints by Early Candidate Pruning -- Comparing MapReduce-Based k-NN Similarity Joins On Hadoop For High-dimensional Data -- A Higher-Fidelity Frugal Quantile Estimator -- Recommender System -- Fair Recommendations Through Diversity Promotion -- A Hierarchical Bayesian Factorization Model for Implicit and Explicit Feedback Data -- Empirical Analysis of Factors Influencing Twitter Hashtag Recommendation on Detected Communities -- Group Recommender Model Based on Preference Interaction -- Identification of Grey Sheep Users By Histogram Intersection In Recommender Systems -- Social Network and Social Media -- A Feature-based Approach for the Redefined Link Prediction Problem in Signed Networks -- From Mutual Friends to Overlapping Community Detection: A Non-negative Matrix Factorization Approach -- Calling for Response: Automatically Distinguishing Situation-aware Tweets During Crises -- Efficient Revenue Maximization for Viral Marketing in Social Networks -- Generating Life Course Trajectory Sequences with Recurrent Neural Networks and Application to Early Detection on Social Disadvantage -- FRISK: A Multilingual Approach to Find twitteR InterestS via wiKipedia -- A Solution to Tweet-Based User Identification across Online Social Networks -- Machine Learning -- Supervised Feature Selection Algorithm Based on Low-Rank and Manifold Learning -- Mixed Membership Sparse Gaussian Conditional Random Fields -- Effects of Dynamic Subspacing in Random Forest -- Diversity and Locality in Multi-Component, Multi-Layer Predictive Systems: A Mutual Information Based Approach -- Hybrid Subspace Mixture Models For Prediction and Anomaly Detection in High Dimensions -- Classification and Clustering Methods --  StruClus: Scalable Structural Graph Set Clustering with Representative Sampling -- Employing Hierarchical Clustering and Reinforcement Learning for Attribute-based Zero-Shot Classification -- Environmental Sound Recognition using Masked Conditional Neural Networks -- Analyzing Performance of Classification Techniques in Detecting Epileptic Seizure -- A Framework for Clustering and Dynamic Maintenance of XML Documents -- Language-independent Twitter Classification using Character-based Convolutional Networks -- Behavior Modeling and User Profiling -- Modeling Check-in Behavior with Geographical Neighborhood Influence of Venues -- An empirical study on collective online behaviors of extremist supporters. -Your Moves, Your Device: Establishing Behavior Profiles using Tensors -- An Approach for Identifying Author Profiles of Blogs -- Generating Topics of Interests for Research Communities -- An Evolutionary Approach for Learning Conditional Preference Network from Inconsistent Examples -- Bioinformatic and Medical Data Analysis -- Predicting Clinical Outcomes of Alzheimer's Disease from Complex Brain Networks -- Doctoral Advisor or Medical Condition: Towards Entity-specific Rankings of Knowledge Base Properties -- Multiclass Lung Cancer Diagnosis by Gene Expression Programming and Microarray Datasets -- Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers -- Spatio-temporal Data -- People-Centric Mobile Crowdsensing Platform for Urban Design -- Long-Term User Location Prediction Using Deep Learning and Periodic Pattern Mining -- An Intelligent Weighted Fuzzy Time Series Model Based on A Sine-Cosine Adaptive Human Learning Optimization Algorithm and Its Application to Financial Markets Forecasting -- Mobile Robot Scheduling with Multiple Trips and Time Windows -- Natural Language Processing and Text Mining -- Feature Analysis for Duplicate Detection in Programming QA Communities -- A Joint Human/Machine Process for Coding Events and Conflict Drivers -- Quality Prediction of Newly Proposed Questions in CQA by Leveraging Weakly Supervised Learning -- Improving Chinese Sentiment Analysis via Segmentation-based Representation Using Parallel CNN -- Entity Recognition by Distant Supervision with Soft List Constraint -- Structured Sentiment Analysis -- Data Mining Applications -- Improving Real-Time Bidding Using a Constrained Markov Decision Process -- PowerLSTM: Power Demand Forecasting Using Long Short-Term Memory Neural Network -- Identifying Unreliable Sensors Without a Knowledge of the Ground Truth in Deceptive Environments -- Color-sketch simulator: a guide for color-based visual known-item search -- Applications -- Making Use of External Company Data to Improve the Classification of Bank Transactions -- Mining Load Profile Patterns for Australian Electricity Consumers -- STA: a Spatio-temporal Thematic Analytics Framework for Urban Ground Sensing -- Privacy and Utility Preservation for Location Data Using Stay Region Analysis -- Location-aware Human Activity Recognition -- Demos -- SWYSWYK: a new Sharing Paradigm for the Personal Cloud -- Tools and Infrastructure for Supporting Enterprise Knowledge Graphs -- An Interactive Web-based Toolset for Knowledge Discovery from Short Text Log Data -- Carbon: Forecasting Civil Unrest Events by Monitoring News and Social Media -- A system for Querying and Analyzing Urban Regions -- Detect tracking behavior among trajectory data.
Record Nr. UNISA-996465333903316
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part IV / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part IV / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Autore Kashima Hisashi
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (360 pages)
Disciplina 006.3
Altri autori (Persone) IdeTsuyoshi
PengWen-Chih
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Education—Data processing
Computer science—Mathematics
Computer vision
Computer engineering
Computer networks
Artificial Intelligence
Design and Analysis of Algorithms
Computers and Education
Mathematics of Computing
Computer Vision
Computer Engineering and Networks
Soggetto non controllato Mathematics
ISBN 3-031-33383-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- General Chairs' Preface -- PC Chairs' Preface -- Organization -- Contents - Part IV -- Scientific Data -- Inline Citation Classification Using Peripheral Context and Time-Evolving Augmentation*-12pt -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Cross-Text Attention -- 3.2 Spatial Fusion -- 3.3 Time Evolving Augmentation -- 4 Experiments -- 4.1 Dataset -- 4.2 Implementation Details -- 5 Baselines -- 6 Analysis -- 7 Conclusion -- References -- Social Network Analysis -- Post-it: Augmented Reality Based Group Recommendation with Item Replacement -- 1 Introduction -- 2 Problem Formulation -- 3 STAR3 -- 3.1 Interaction- and Preference-Aware Graph Attention Network -- 3.2 Haptic-Aware Virtual Candidate Item Generator -- 3.3 Social- and Haptic-Aware Recommender -- 3.4 Overall Objective -- 4 Experiments -- 5 Conclusion -- References -- Proactive Rumor Control: When Impression Counts -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 3.1 Influence Model -- 3.2 Influence Block -- 3.3 Problem Definition -- 4 Our Framework -- 4.1 A Baseline -- 4.2 Branch-and-Bound Framework -- 4.3 Computing Upper Bound -- 4.4 Analysis of Solutions -- 5 Progressive Branch-and-Bound -- 6 Experiments -- 6.1 Experimental Settings -- 6.2 Effectiveness Test -- 6.3 Efficiency Test -- 6.4 Scalability Test -- 7 Conclusion -- References -- Spatio-Temporal Data -- Generative-Contrastive-Attentive Spatial-Temporal Network for Traffic Data Imputation -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 The GCASTN Model -- 4.1 Generative-Contrastive Self-Supervised Learning -- 4.2 Data Augmentation via Two-Fold Cross Random Masking -- 4.3 GCASTN Encoder -- 4.4 GCASTN Decoder -- 5 Experiments -- 5.1 Datasets and Baselines -- 5.2 Experimental Results -- 6 Conclusion -- References.
Road Network Representation Learning with Vehicle Trajectories*-12pt -- 1 Introduction -- 2 Problem Definition -- 3 TrajRNE Approach -- 3.1 Spatial Flow Convolution -- 3.2 Structural Road Encoder -- 3.3 TrajRNE Overview -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Downstream Tasks and Evaluation Metrics -- 4.4 Experimental Settings -- 4.5 Performance Results -- 4.6 Ablation Study -- 4.7 Parameter Study -- 5 Related Work -- 6 Conclusion -- References -- MetaCitta: Deep Meta-Learning for Spatio-Temporal Prediction Across Cities and Tasks*-12pt -- 1 Introduction -- 2 Problem Statement -- 3 The MetaCitta Approach -- 3.1 Spatial Encoder -- 3.2 Temporal Encoder -- 3.3 Prediction -- 3.4 Training Procedure -- 4 Evaluation Setup -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Experimental Settings -- 5 Evaluation -- 5.1 Comparison with Baselines -- 5.2 Ablation Study -- 5.3 Training Time Comparison -- 6 Related Work -- 7 Conclusion -- References -- Deep Graph Stream SVDD: Anomaly Detection in Cyber-Physical Systems -- 1 Introduction -- 2 Preliminaries -- 2.1 Definitions -- 2.2 Problem Statement -- 3 Methodology -- 3.1 Framework Overview -- 3.2 Embedding Temporal Patterns of the Graph Stream Data -- 3.3 Generating Dynamic Weighted Attributed Graphs -- 3.4 Representation Learning for Weighted Attributed Graph -- 3.5 One-Class Detection with SVDD -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 5 Related Work -- 6 Conclusion -- References -- Texts, Web, Social Media -- Words Can Be Confusing: Stereotype Bias Removal in Text Classification at the Word Level -- 1 Introduction -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Stereotype Words Detection -- 2.3 Fusion Model Training -- 2.4 Unbiased Prediction -- 3 Experiments -- 3.1 Settings -- 3.2 Classification Performance -- 3.3 Stereotype Word Fairness.
3.4 Proportion of Stereotype Words -- 4 Conclusion -- References -- Knowledge-Enhanced Hierarchical Transformers for Emotion-Cause Pair Extraction -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Overall Architecture -- 3.2 Commonsense Knowledge Injection -- 3.3 Knowledge-Enhanced Clause Encoding -- 3.4 Emotion-Cause Pair Extraction -- 4 Experiments -- 4.1 Datasets and Metrics -- 4.2 Baselines -- 4.3 Implementation Details -- 4.4 Comparison with ECPE Methods -- 5 Conclusion and Future Work -- References -- PICKD: In-Situ Prompt Tuning for Knowledge-Grounded Dialogue Generation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Formal Problem Definition -- 3.2 Contextual Prompting for Knowledge Selection -- 3.3 BART Fine-Tuning for Response Generation -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Baseline Methods -- 4.3 Evaluation Metrics -- 4.4 Implementation Details -- 5 Empirical Results -- 5.1 Automatic Evaluation -- 5.2 Impact of Prompt Length -- 5.3 Impact of Knowledge Length -- 5.4 Manual Evaluation -- 5.5 Error Analysis -- 6 Conclusion -- References -- Fake News Detection Through Temporally Evolving User Interactions -- 1 Introduction -- 2 Problem Formulation and Data Structure -- 3 Proposed Model -- 3.1 Local Sub-graph Encoding Module -- 3.2 Global Evolution Capturing Module -- 3.3 Neural Hawkes Process Module -- 3.4 Model Training -- 4 Experiment -- 4.1 Datasets -- 4.2 Baseline Methods -- 4.3 Experiment Setting -- 4.4 Performance Comparison -- 4.5 Ablation Study -- 4.6 Early Detection Performance -- 4.7 Case Study -- 5 Related Work -- 6 Conclusion -- References -- Improving Machine Translation and Summarization with the Sinkhorn Divergence*-12pt -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Sequence-to-Sequence Model Training -- 3.2 The Proposed Approach: A Contextual Sinkhorn Divergence.
4 Experiments -- 4.1 Datasets -- 4.2 Models and Training -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Dual-Detector: An Unsupervised Learning Framework for Chinese Spelling Check -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Hybrid Mask Strategy -- 2.3 Detector Dec-Err -- 2.4 Candidate Table -- 2.5 Detector Dec-Eva -- 2.6 Training -- 3 Experiments -- 3.1 Datasets and Settings -- 3.2 Main Results -- 3.3 Analysis -- 4 Conclusion -- References -- QA-Matcher: Unsupervised Entity Matching Using a Question Answering Model -- 1 Introduction -- 2 Preliminaries -- 2.1 Question Answering -- 3 Proposed Method -- 3.1 Idea: Solving Entity Matching as Question Answering -- 3.2 Problem Setting -- 3.3 Framework -- 3.4 Retriever -- 3.5 Question and Passage Prompts -- 3.6 QA Classification -- 3.7 Reclassification -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Results -- 4.3 Ablation Study -- 4.4 Sensitivity Analysis -- 5 Related Work -- 6 Conclusion -- References -- Multi-task Student Teacher Based Unsupervised Domain Adaptation for Address Parsing -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Adaptive Pre-training Using MLM -- 3.2 Student-Teacher Framework -- 3.3 Consistency Regularisation Task -- 3.4 Boundary Detection Task -- 4 Experiments, Data and Results -- 4.1 Data -- 4.2 Experiment Setup -- 4.3 Baselines -- 4.4 Results, Ablation Studies, Parameter Study and Case Study -- 4.5 Training/Inference Time -- 5 Industrial Usecase -- 6 Conclusion and Future Work -- References -- Generative Sentiment Transfer via Adaptive Masking -- 1 Introduction -- 2 Problem Definition -- 3 Methodology -- 3.1 Framework -- 3.2 Adaptive Sentiment Token Masking -- 3.3 Infilling Blanks -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Quantitative Analysis -- 4.3 Ablation Study -- 4.4 Parameter Sensitivity Analysis -- 5 Conclusion.
References -- Unsupervised Text Style Transfer Through Differentiable Back Translation and Rewards -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Problem Definition -- 3.2 Shared Encoding -- 3.3 Auto-Encoding -- 3.4 Differentiable Back-Translation -- 3.5 Reinforcement Learning -- 3.6 Learning Technique -- 4 Datasets, Experiments and Results -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Automatic and Human Evaluation -- 5 Analysis -- 5.1 Ablation Studies -- 5.2 Case Study -- 5.3 Error Analysis -- 6 Conclusion and Future Works -- References -- Exploiting Phrase Interrelations in Span-level Neural Approaches for Aspect Sentiment Triplet Extraction*-12pt -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Contextual Input Representation -- 3.2 Span Construction -- 3.3 Span Filtering -- 3.4 Triplet Construction -- 3.5 Model Training -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Summary -- References -- What Boosts Fake News Dissemination on Social Media? A Causal Inference View -- 1 Introduction -- 2 Problem Definition -- 3 Our Framework -- 3.1 Preliminary -- 3.2 Causal Feature Representation Learning -- 3.3 Multimodal Covariates Embedding -- 4 Experiment -- 4.1 Evaluation Datasets -- 4.2 Experiment Setting -- 4.3 Main Results -- 4.4 Lexicons Boosting Dissemination -- 5 Related Work -- 6 Conclusion -- References -- Topic-Selective Graph Network for Topic-Focused Summarization -- 1 Introduction -- 2 Related Work -- 2.1 PLM-based Summarization -- 2.2 Topic-Guided Summarization -- 2.3 Graph Neural Network -- 3 Method -- 3.1 Base Topic-Focused Summarization Model -- 3.2 Topic-Arc Recognition -- 3.3 Summarization with Topic-Selective Graph Network -- 3.4 Training -- 4 Experiments -- 4.1 Dataset and Evaluation Metrics -- 4.2 Experimental Setting -- 4.3 Main Results -- 4.4 Ablation Study.
4.5 Impact of Topic Node.
Record Nr. UNINA-9910728400103321
Kashima Hisashi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part III / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part III / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Autore Kashima Hisashi
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (419 pages)
Disciplina 006.312
Altri autori (Persone) IdeTsuyoshi
PengWen-Chih
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Education—Data processing
Computer science—Mathematics
Computer vision
Computer engineering
Computer networks
Artificial Intelligence
Design and Analysis of Algorithms
Computers and Education
Mathematics of Computing
Computer Vision
Computer Engineering and Networks
Soggetto non controllato Mathematics
ISBN 3-031-33380-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Big data -- Toward Explainable Recommendation Via Counterfactual Reasoning -- Online Volume Optimization for Notifications via Long Short-Term Value Modeling -- Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases -- Financial data -- Joint Latent Topic Discovery and Expectation Modeling for Financial Markets -- Let the model make financial senses: a Text2Text generative approach for financial complaint identification -- Information retrieval and search -- Web-scale Semantic Product Search With Large Language Models -- Multi-task learning based Keywords weighted Siamese Model for semantic retrieval -- Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion -- MFBE: Leveraging Multi-Field Information of FAQs for Efficient Dense Retrieval -- Isotropic Representation Can Improve Dense Retrieval -- Knowledge-Enhanced Prototypical Network with Structural Semantics for Few-Shot Relation Classification -- Internet of Things -- MIDFA : Memory-Based Instance Division and Feature Aggregation Network for Video Object Detection -- Medical and biological data -- Vision Transformers for Small Histological Datasets learned through Knowledge Distillation -- Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis -- DKFM: Dual Knowledge-guided Fusion Model for Drug Recommendation -- Hierarchical Graph Neural Network for Patient Treatment Preference Prediction with External Knowledge -- Multimedia and multimodal data -- An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition Performance -- Dynamically-Scaled Deep Canonical Correlation Analysis -- TCR: Short Video Title Generation and Cover Selection with Attention Refinement -- ItrievalKD: An Iterative Retrieval Framework Assisted with Knowledge Distillation for Noisy Text-to-Image Retrieval -- Recommender systems -- Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations -- Interest Driven Graph Structure Learning for Session-Based Recommendation -- Multi-behavior Guided Temporal Graph Attention Network for Recommendation -- Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation -- Meta-learning Enhanced Next POI Recommendation by Leveraging Check-ins from Auxiliary Cities -- Global-Aware External Attention Deep Model for Sequential Recommendation -- Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking -- Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation -- kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval -- Staying or Leaving: A Knowledge-Enhanced User Simulator for Reinforcement Learning Based Short Video Recommendation -- RLMixer: A Reinforcement Learning Approach For Integrated Ranking With Contrastive User Preference Modeling.
Record Nr. UNINA-9910728399703321
Kashima Hisashi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Autore Kashima Hisashi
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (563 pages)
Disciplina 006.312
Altri autori (Persone) IdeTsuyoshi
PengWen-Chih
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Education—Data processing
Computer science—Mathematics
Computer vision
Computer engineering
Computer networks
Artificial Intelligence
Design and Analysis of Algorithms
Computers and Education
Mathematics of Computing
Computer Vision
Computer Engineering and Networks
Soggetto non controllato Mathematics
ISBN 3-031-33374-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996534464203316
Kashima Hisashi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part III / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part III / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Autore Kashima Hisashi
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (419 pages)
Disciplina 006.312
Altri autori (Persone) IdeTsuyoshi
PengWen-Chih
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Education—Data processing
Computer science—Mathematics
Computer vision
Computer engineering
Computer networks
Artificial Intelligence
Design and Analysis of Algorithms
Computers and Education
Mathematics of Computing
Computer Vision
Computer Engineering and Networks
Soggetto non controllato Mathematics
ISBN 3-031-33380-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Big data -- Toward Explainable Recommendation Via Counterfactual Reasoning -- Online Volume Optimization for Notifications via Long Short-Term Value Modeling -- Discovering Geo-referenced Frequent Patterns in Uncertain Geo-referenced Transactional Databases -- Financial data -- Joint Latent Topic Discovery and Expectation Modeling for Financial Markets -- Let the model make financial senses: a Text2Text generative approach for financial complaint identification -- Information retrieval and search -- Web-scale Semantic Product Search With Large Language Models -- Multi-task learning based Keywords weighted Siamese Model for semantic retrieval -- Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion -- MFBE: Leveraging Multi-Field Information of FAQs for Efficient Dense Retrieval -- Isotropic Representation Can Improve Dense Retrieval -- Knowledge-Enhanced Prototypical Network with Structural Semantics for Few-Shot Relation Classification -- Internet of Things -- MIDFA : Memory-Based Instance Division and Feature Aggregation Network for Video Object Detection -- Medical and biological data -- Vision Transformers for Small Histological Datasets learned through Knowledge Distillation -- Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis -- DKFM: Dual Knowledge-guided Fusion Model for Drug Recommendation -- Hierarchical Graph Neural Network for Patient Treatment Preference Prediction with External Knowledge -- Multimedia and multimodal data -- An Extended Variational Mode Decomposition Algorithm Developed Speech Emotion Recognition Performance -- Dynamically-Scaled Deep Canonical Correlation Analysis -- TCR: Short Video Title Generation and Cover Selection with Attention Refinement -- ItrievalKD: An Iterative Retrieval Framework Assisted with Knowledge Distillation for Noisy Text-to-Image Retrieval -- Recommender systems -- Semantic Relation Transfer for Non-overlapped Cross-domain Recommendations -- Interest Driven Graph Structure Learning for Session-Based Recommendation -- Multi-behavior Guided Temporal Graph Attention Network for Recommendation -- Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation -- Meta-learning Enhanced Next POI Recommendation by Leveraging Check-ins from Auxiliary Cities -- Global-Aware External Attention Deep Model for Sequential Recommendation -- Aggregately Diversified Bundle Recommendation via Popularity Debiasing and Configuration-aware Reranking -- Diversely Regularized Matrix Factorization for Accurate and Aggregately Diversified Recommendation -- kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval -- Staying or Leaving: A Knowledge-Enhanced User Simulator for Reinforcement Learning Based Short Video Recommendation -- RLMixer: A Reinforcement Learning Approach For Integrated Ranking With Contrastive User Preference Modeling.
Record Nr. UNISA-996534464303316
Kashima Hisashi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
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Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part IV / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part IV / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Autore Kashima Hisashi
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (360 pages)
Disciplina 006.3
Altri autori (Persone) IdeTsuyoshi
PengWen-Chih
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Education—Data processing
Computer science—Mathematics
Computer vision
Computer engineering
Computer networks
Artificial Intelligence
Design and Analysis of Algorithms
Computers and Education
Mathematics of Computing
Computer Vision
Computer Engineering and Networks
Soggetto non controllato Mathematics
ISBN 3-031-33383-7
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- General Chairs' Preface -- PC Chairs' Preface -- Organization -- Contents - Part IV -- Scientific Data -- Inline Citation Classification Using Peripheral Context and Time-Evolving Augmentation*-12pt -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Cross-Text Attention -- 3.2 Spatial Fusion -- 3.3 Time Evolving Augmentation -- 4 Experiments -- 4.1 Dataset -- 4.2 Implementation Details -- 5 Baselines -- 6 Analysis -- 7 Conclusion -- References -- Social Network Analysis -- Post-it: Augmented Reality Based Group Recommendation with Item Replacement -- 1 Introduction -- 2 Problem Formulation -- 3 STAR3 -- 3.1 Interaction- and Preference-Aware Graph Attention Network -- 3.2 Haptic-Aware Virtual Candidate Item Generator -- 3.3 Social- and Haptic-Aware Recommender -- 3.4 Overall Objective -- 4 Experiments -- 5 Conclusion -- References -- Proactive Rumor Control: When Impression Counts -- 1 Introduction -- 2 Related Work -- 3 Problem Formulation -- 3.1 Influence Model -- 3.2 Influence Block -- 3.3 Problem Definition -- 4 Our Framework -- 4.1 A Baseline -- 4.2 Branch-and-Bound Framework -- 4.3 Computing Upper Bound -- 4.4 Analysis of Solutions -- 5 Progressive Branch-and-Bound -- 6 Experiments -- 6.1 Experimental Settings -- 6.2 Effectiveness Test -- 6.3 Efficiency Test -- 6.4 Scalability Test -- 7 Conclusion -- References -- Spatio-Temporal Data -- Generative-Contrastive-Attentive Spatial-Temporal Network for Traffic Data Imputation -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 4 The GCASTN Model -- 4.1 Generative-Contrastive Self-Supervised Learning -- 4.2 Data Augmentation via Two-Fold Cross Random Masking -- 4.3 GCASTN Encoder -- 4.4 GCASTN Decoder -- 5 Experiments -- 5.1 Datasets and Baselines -- 5.2 Experimental Results -- 6 Conclusion -- References.
Road Network Representation Learning with Vehicle Trajectories*-12pt -- 1 Introduction -- 2 Problem Definition -- 3 TrajRNE Approach -- 3.1 Spatial Flow Convolution -- 3.2 Structural Road Encoder -- 3.3 TrajRNE Overview -- 4 Experimental Evaluation -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Downstream Tasks and Evaluation Metrics -- 4.4 Experimental Settings -- 4.5 Performance Results -- 4.6 Ablation Study -- 4.7 Parameter Study -- 5 Related Work -- 6 Conclusion -- References -- MetaCitta: Deep Meta-Learning for Spatio-Temporal Prediction Across Cities and Tasks*-12pt -- 1 Introduction -- 2 Problem Statement -- 3 The MetaCitta Approach -- 3.1 Spatial Encoder -- 3.2 Temporal Encoder -- 3.3 Prediction -- 3.4 Training Procedure -- 4 Evaluation Setup -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Experimental Settings -- 5 Evaluation -- 5.1 Comparison with Baselines -- 5.2 Ablation Study -- 5.3 Training Time Comparison -- 6 Related Work -- 7 Conclusion -- References -- Deep Graph Stream SVDD: Anomaly Detection in Cyber-Physical Systems -- 1 Introduction -- 2 Preliminaries -- 2.1 Definitions -- 2.2 Problem Statement -- 3 Methodology -- 3.1 Framework Overview -- 3.2 Embedding Temporal Patterns of the Graph Stream Data -- 3.3 Generating Dynamic Weighted Attributed Graphs -- 3.4 Representation Learning for Weighted Attributed Graph -- 3.5 One-Class Detection with SVDD -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Experimental Results -- 5 Related Work -- 6 Conclusion -- References -- Texts, Web, Social Media -- Words Can Be Confusing: Stereotype Bias Removal in Text Classification at the Word Level -- 1 Introduction -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Stereotype Words Detection -- 2.3 Fusion Model Training -- 2.4 Unbiased Prediction -- 3 Experiments -- 3.1 Settings -- 3.2 Classification Performance -- 3.3 Stereotype Word Fairness.
3.4 Proportion of Stereotype Words -- 4 Conclusion -- References -- Knowledge-Enhanced Hierarchical Transformers for Emotion-Cause Pair Extraction -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Overall Architecture -- 3.2 Commonsense Knowledge Injection -- 3.3 Knowledge-Enhanced Clause Encoding -- 3.4 Emotion-Cause Pair Extraction -- 4 Experiments -- 4.1 Datasets and Metrics -- 4.2 Baselines -- 4.3 Implementation Details -- 4.4 Comparison with ECPE Methods -- 5 Conclusion and Future Work -- References -- PICKD: In-Situ Prompt Tuning for Knowledge-Grounded Dialogue Generation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Formal Problem Definition -- 3.2 Contextual Prompting for Knowledge Selection -- 3.3 BART Fine-Tuning for Response Generation -- 4 Experimental Setup -- 4.1 Datasets -- 4.2 Baseline Methods -- 4.3 Evaluation Metrics -- 4.4 Implementation Details -- 5 Empirical Results -- 5.1 Automatic Evaluation -- 5.2 Impact of Prompt Length -- 5.3 Impact of Knowledge Length -- 5.4 Manual Evaluation -- 5.5 Error Analysis -- 6 Conclusion -- References -- Fake News Detection Through Temporally Evolving User Interactions -- 1 Introduction -- 2 Problem Formulation and Data Structure -- 3 Proposed Model -- 3.1 Local Sub-graph Encoding Module -- 3.2 Global Evolution Capturing Module -- 3.3 Neural Hawkes Process Module -- 3.4 Model Training -- 4 Experiment -- 4.1 Datasets -- 4.2 Baseline Methods -- 4.3 Experiment Setting -- 4.4 Performance Comparison -- 4.5 Ablation Study -- 4.6 Early Detection Performance -- 4.7 Case Study -- 5 Related Work -- 6 Conclusion -- References -- Improving Machine Translation and Summarization with the Sinkhorn Divergence*-12pt -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Sequence-to-Sequence Model Training -- 3.2 The Proposed Approach: A Contextual Sinkhorn Divergence.
4 Experiments -- 4.1 Datasets -- 4.2 Models and Training -- 4.3 Results and Discussion -- 5 Conclusion -- References -- Dual-Detector: An Unsupervised Learning Framework for Chinese Spelling Check -- 1 Introduction -- 2 Method -- 2.1 Overview -- 2.2 Hybrid Mask Strategy -- 2.3 Detector Dec-Err -- 2.4 Candidate Table -- 2.5 Detector Dec-Eva -- 2.6 Training -- 3 Experiments -- 3.1 Datasets and Settings -- 3.2 Main Results -- 3.3 Analysis -- 4 Conclusion -- References -- QA-Matcher: Unsupervised Entity Matching Using a Question Answering Model -- 1 Introduction -- 2 Preliminaries -- 2.1 Question Answering -- 3 Proposed Method -- 3.1 Idea: Solving Entity Matching as Question Answering -- 3.2 Problem Setting -- 3.3 Framework -- 3.4 Retriever -- 3.5 Question and Passage Prompts -- 3.6 QA Classification -- 3.7 Reclassification -- 4 Experiments -- 4.1 Experimental Settings -- 4.2 Results -- 4.3 Ablation Study -- 4.4 Sensitivity Analysis -- 5 Related Work -- 6 Conclusion -- References -- Multi-task Student Teacher Based Unsupervised Domain Adaptation for Address Parsing -- 1 Introduction -- 2 Related Work -- 3 Proposed Methodology -- 3.1 Adaptive Pre-training Using MLM -- 3.2 Student-Teacher Framework -- 3.3 Consistency Regularisation Task -- 3.4 Boundary Detection Task -- 4 Experiments, Data and Results -- 4.1 Data -- 4.2 Experiment Setup -- 4.3 Baselines -- 4.4 Results, Ablation Studies, Parameter Study and Case Study -- 4.5 Training/Inference Time -- 5 Industrial Usecase -- 6 Conclusion and Future Work -- References -- Generative Sentiment Transfer via Adaptive Masking -- 1 Introduction -- 2 Problem Definition -- 3 Methodology -- 3.1 Framework -- 3.2 Adaptive Sentiment Token Masking -- 3.3 Infilling Blanks -- 4 Experiment -- 4.1 Experimental Settings -- 4.2 Quantitative Analysis -- 4.3 Ablation Study -- 4.4 Parameter Sensitivity Analysis -- 5 Conclusion.
References -- Unsupervised Text Style Transfer Through Differentiable Back Translation and Rewards -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Problem Definition -- 3.2 Shared Encoding -- 3.3 Auto-Encoding -- 3.4 Differentiable Back-Translation -- 3.5 Reinforcement Learning -- 3.6 Learning Technique -- 4 Datasets, Experiments and Results -- 4.1 Datasets -- 4.2 Baselines -- 4.3 Automatic and Human Evaluation -- 5 Analysis -- 5.1 Ablation Studies -- 5.2 Case Study -- 5.3 Error Analysis -- 6 Conclusion and Future Works -- References -- Exploiting Phrase Interrelations in Span-level Neural Approaches for Aspect Sentiment Triplet Extraction*-12pt -- 1 Introduction -- 2 Related Works -- 3 Proposed Method -- 3.1 Contextual Input Representation -- 3.2 Span Construction -- 3.3 Span Filtering -- 3.4 Triplet Construction -- 3.5 Model Training -- 4 Experimental Evaluation -- 4.1 Experimental Setup -- 4.2 Results -- 5 Summary -- References -- What Boosts Fake News Dissemination on Social Media? A Causal Inference View -- 1 Introduction -- 2 Problem Definition -- 3 Our Framework -- 3.1 Preliminary -- 3.2 Causal Feature Representation Learning -- 3.3 Multimodal Covariates Embedding -- 4 Experiment -- 4.1 Evaluation Datasets -- 4.2 Experiment Setting -- 4.3 Main Results -- 4.4 Lexicons Boosting Dissemination -- 5 Related Work -- 6 Conclusion -- References -- Topic-Selective Graph Network for Topic-Focused Summarization -- 1 Introduction -- 2 Related Work -- 2.1 PLM-based Summarization -- 2.2 Topic-Guided Summarization -- 2.3 Graph Neural Network -- 3 Method -- 3.1 Base Topic-Focused Summarization Model -- 3.2 Topic-Arc Recognition -- 3.3 Summarization with Topic-Selective Graph Network -- 3.4 Training -- 4 Experiments -- 4.1 Dataset and Evaluation Metrics -- 4.2 Experimental Setting -- 4.3 Main Results -- 4.4 Ablation Study.
4.5 Impact of Topic Node.
Record Nr. UNISA-996534463803316
Kashima Hisashi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Advances in Knowledge Discovery and Data Mining [[electronic resource] ] : 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I / / edited by Hisashi Kashima, Tsuyoshi Ide, Wen-Chih Peng
Autore Kashima Hisashi
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Descrizione fisica 1 online resource (563 pages)
Disciplina 006.312
Altri autori (Persone) IdeTsuyoshi
PengWen-Chih
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Artificial intelligence
Algorithms
Education—Data processing
Computer science—Mathematics
Computer vision
Computer engineering
Computer networks
Artificial Intelligence
Design and Analysis of Algorithms
Computers and Education
Mathematics of Computing
Computer Vision
Computer Engineering and Networks
Soggetto non controllato Mathematics
ISBN 3-031-33374-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910728396003321
Kashima Hisashi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks : Nov. 2, 2010, San Jose, CA, USA
Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Location Based Social Networks : Nov. 2, 2010, San Jose, CA, USA
Autore Zhou Xiaofang
Pubbl/distr/stampa [Place of publication not identified], : ACM, 2010
Descrizione fisica 1 online resource (80 pages)
Collana ACM Conferences
Soggetto topico Electrical & Computer Engineering
Engineering & Applied Sciences
Telecommunications
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Proceedings of the 2nd Association for Computing Machinery Special Interest Group on Spatial Information International Workshop on Location Based Social Networks : November 2, 2010, San Jose, California, United States of America
GIS '10 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, San Jose, CA, USA - November 03 - 05, 2010
Record Nr. UNINA-9910376028203321
Zhou Xiaofang  
[Place of publication not identified], : ACM, 2010
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Trends and Applications in Knowledge Discovery and Data Mining [[electronic resource] ] : PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers / / edited by Wen-Chih Peng, Haixun Wang, James Bailey, Vincent S. Tseng, Tu Bao Ho, Zhi-Hua Zhou, Arbee L.P. Chen
Trends and Applications in Knowledge Discovery and Data Mining [[electronic resource] ] : PAKDD 2014 International Workshops: DANTH, BDM, MobiSocial, BigEC, CloudSD, MSMV-MBI, SDA, DMDA-Health, ALSIP, SocNet, DMBIH, BigPMA,Tainan, Taiwan, May 13-16, 2014. Revised Selected Papers / / edited by Wen-Chih Peng, Haixun Wang, James Bailey, Vincent S. Tseng, Tu Bao Ho, Zhi-Hua Zhou, Arbee L.P. Chen
Edizione [1st ed. 2014.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Descrizione fisica 1 online resource (XXI, 833 p. 348 illus.)
Disciplina 006.312
Collana Lecture Notes in Artificial Intelligence
Soggetto topico Data mining
Artificial intelligence
Health informatics
Information storage and retrieval
Application software
Data Mining and Knowledge Discovery
Artificial Intelligence
Health Informatics
Information Storage and Retrieval
Information Systems Applications (incl. Internet)
ISBN 3-319-13186-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Data Analytics for Targeted Healthcare, DANTH -- Data Mining and Decision Analytics for Public Health and Wellness, DMDA-Health -- Biologically Inspired Data Mining Techniques, BDM -- Mobile Data Management, Mining, and Computing on Social Networks, MobiSocial -- Big Data Science and Engineering on E-Commerce, BigEC -- Cloud Service Discovery, CloudSD -- Mobile Sensing, Mining and Visualization for Human Behavior Inferences, MSMV-HBI -- Scalable Dats Analytics: Theory and Algorithms, SDA -- Algorithms for Large-Scale Information Processing in Knowledge Discovery, ALSIP -- Data Mining in Social Networks, SocNet -- Data Mining in Biomedical Informatics and Healthcare, DMBIH.- Pattern Mining and Application of Big Data, BigPMA.
Record Nr. UNINA-9910483991803321
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2014
Materiale a stampa
Lo trovi qui: Univ. Federico II
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