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Complex Pattern Mining : New Challenges, Methods and Applications / / edited by Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras
| Complex Pattern Mining : New Challenges, Methods and Applications / / edited by Annalisa Appice, Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (x, 250 pages) : illustrations |
| Disciplina | 006.3 |
| Collana | Studies in Computational Intelligence |
| Soggetto topico |
Computational intelligence
Artificial intelligence Data mining Pattern recognition systems Computational Intelligence Artificial Intelligence Data Mining and Knowledge Discovery Automated Pattern Recognition |
| ISBN | 3-030-36617-0 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Efficient Infrequent Pattern Mining using Negative Itemset Tree -- Hierarchical Adversarial Training for Multi-Domain -- Optimizing C-index via Gradient Boosting in Medical Survival Analysis -- Order-preserving Biclustering Based on FCA and Pattern Structures -- A text-based regression approach to predict bug-fix time -- A Named Entity Recognition Approach for Albanian Using Deep Learning -- A Latitudinal Study on the Use of Sequential and Concurrency Patterns in Deviance Mining -- Efficient Declarative-based Process Mining using an Enhanced Framework -- Exploiting Pattern Set Dissimilarity for Detecting Changes in Communication Networks -- Classification and Clustering of Emotive Microblogs in Albanian: Two User-Oriented Tasks. |
| Record Nr. | UNINA-9910484953003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database and Expert Systems Applications : 35th International Conference, DEXA 2024, Naples, Italy, August 26–28, 2024, Proceedings, Part II / / edited by Christine Strauss, Toshiyuki Amagasa, Giuseppe Manco, Gabriele Kotsis, A Min Tjoa, Ismail Khalil
| Database and Expert Systems Applications : 35th International Conference, DEXA 2024, Naples, Italy, August 26–28, 2024, Proceedings, Part II / / edited by Christine Strauss, Toshiyuki Amagasa, Giuseppe Manco, Gabriele Kotsis, A Min Tjoa, Ismail Khalil |
| Autore | Strauss Christine |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (337 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
AmagasaToshiyuki
MancoGiuseppe KotsisGabriele TjoaA. Min KhalilIsmail |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Database management
Artificial intelligence Information technology - Management Software engineering Information storage and retrieval systems Data mining Database Management Artificial Intelligence Computer Application in Administrative Data Processing Software Engineering Information Storage and Retrieval Data Mining and Knowledge Discovery |
| ISBN |
9783031683121
9783031683114 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910881087703321 |
Strauss Christine
|
||
| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Database and Expert Systems Applications : 35th International Conference, DEXA 2024, Naples, Italy, August 26–28, 2024, Proceedings, Part I / / edited by Christine Strauss, Toshiyuki Amagasa, Giuseppe Manco, Gabriele Kotsis, A Min Tjoa, Ismail Khalil
| Database and Expert Systems Applications : 35th International Conference, DEXA 2024, Naples, Italy, August 26–28, 2024, Proceedings, Part I / / edited by Christine Strauss, Toshiyuki Amagasa, Giuseppe Manco, Gabriele Kotsis, A Min Tjoa, Ismail Khalil |
| Autore | Strauss Christine |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (289 pages) |
| Disciplina | 005.74 |
| Altri autori (Persone) |
AmagasaToshiyuki
MancoGiuseppe KotsisGabriele TjoaA. Min KhalilIsmail |
| Collana | Lecture Notes in Computer Science |
| Soggetto topico |
Database management
Artificial intelligence Information technology - Management Software engineering Information storage and retrieval systems Data mining Database Management Artificial Intelligence Computer Application in Administrative Data Processing Software Engineering Information Storage and Retrieval Data Mining and Knowledge Discovery |
| ISBN |
9783031683091
9783031683084 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Organization -- Abstracts of Keynote Talks -- Multimodal Deep Learning in Medical Imaging -- Digital Humanism as an Enabler for a Holistic Socio-Technical Approach to the Latest Developments in Computer Science and Artificial Intelligence -- Deep Entity Processing in the Era of Large Language Models: Challenges and Opportunities -- Contents - Part I -- Contents - Part II -- Financial and Economic Data Analysis -- CSPRD: A Financial Policy Retrieval Dataset for Chinese Stock Market -- 1 Introduction -- 2 Related Work -- 2.1 Retrieval Augmented Generation -- 2.2 Dense Retrievers -- 2.3 Specialised Financial Datasets -- 3 The Policy Retrieval Dataset for Stock Market in China -- 3.1 Data Collection -- 3.2 Data Processing -- 3.3 Unsupervised MoE Selection -- 3.4 Expert Annotation -- 3.5 Dataset Release -- 4 CSPR-MQA Pre-training -- 4.1 Data Preprocessing -- 4.2 Encoding -- 4.3 Decoding -- 5 Experiments -- 5.1 Models -- 5.2 Evaluation Metrics -- 5.3 Results and Analysis -- 6 Limitations -- 6.1 Compromise Between Labor Costs and Decision Comprehensiveness -- 6.2 Limited Experiments on Pre-Trained Language Models -- 7 Conclusion -- References -- Leveraging Heterogeneous Text Data for Reinforcement Learning-Based Stock Trading Strategies -- 1 Introduction -- 2 Related Work -- 3 Preliminaries -- 3.1 Terms -- 3.2 Problem Definition -- 3.3 Base Model -- 4 Proposed Method -- 4.1 Encording -- 4.2 Feature Generation -- 4.3 Action Determination -- 5 Experiment -- 5.1 Datasets -- 5.2 Experimental Setup -- 5.3 Experimental Results -- 5.4 Comparison with Index-Based Method -- 5.5 Effects of Periods and Initial Assets -- 6 Conclusion -- References -- TCMIDP: A Comprehensive Database of Traditional Chinese Medicine for Network Pharmacology Research -- 1 Introduction -- 2 Database Contents and Access -- 3 Data Mining -- 4 User Evaluation.
5 Conclusion -- References -- Graph Theory and Network Analysis -- Fast Subgraph Search with Graph Code Indices -- 1 Introduction -- 2 Preliminaries -- 3 Related Work -- 4 Basic Concept of the Proposed Method -- 5 Graph Representation and Indexing of Databases -- 6 Subgraph Search with the Code Tree -- 7 Experimental Evaluation -- 7.1 Experimental Settings -- 7.2 Experimental Results -- 8 Conclusion -- References -- Completing Predicates Based on Alignment Rules from Knowledge Graphs -- 1 Introduction -- 2 Motivating Example -- 3 The SYRUP Approach -- 4 Experimental Study -- 5 Related Work -- 6 Conclusions and Future Work -- References -- Enriching Hierarchical Navigable Small World Searches with Result Diversification -- 1 Introduction -- 2 Preliminaries and Related Work -- 3 Material and Methods -- 4 Empirical Evaluation -- 5 Conclusions -- References -- An Efficient Indexing Method for Dynamic Graph kNN -- 1 Introduction -- 1.1 Existing Approaches and Challenges -- 1.2 Our Approaches and Contributions -- 2 Preliminary -- 2.1 Problem Definition -- 2.2 Previous Method: CT Index -- 3 Proposed Method: Dynamic CT -- 3.1 Ideas -- 3.2 Adding Nodes and Edges -- 3.3 Removing Nodes and Edges -- 3.4 Complexity Analysis -- 4 Experimental Evaluation -- 4.1 Efficiency for Updating -- 4.2 Efficiency for Adding/Removing Edges -- 5 Conclusion -- References -- Database Management and Query Optimization -- Improving the Accuracy of Text-to-SQL Tools Based on Large Language Models for Real-World Relational Databases -- 1 Introduction -- 2 Related Work -- 3 A Real-World Benchmark for the Text-to-SQL Task -- 3.1 The Real-World Relational Database -- 3.2 The Sets of Views -- 3.3 The Test Questions and Their Ground Truth SQL Translations -- 4 The Proposed RAG-Based Technique -- 4.1 Generation of the Synthetic Dataset -- 4.2 The Proposed RAG-Based Techniques. 5 Experiments with an RW-RDB -- 5.1 Experimental Setup -- 5.2 Results -- 6 Experiments with Mondial -- 7 Conclusions -- References -- QPSEncoder: A Database Workload Encoder with Deep Learning -- 1 Introduction -- 2 Related Work -- 3 QPSEncoder Framework -- 3.1 Physical Plan Encoding -- 3.2 SQL Query Encoding -- 3.3 Database Schema Encoding -- 4 Experiments -- 4.1 Experimental Setup -- 4.2 Effectiveness of QPSEncoder on Numeric Predicates. -- 4.3 Effectiveness of QPSEncoder on Mixed Predicates. -- 4.4 Effectiveness of Model Components -- 5 Conclusion -- References -- Efficient Random Sampling from Very Large Databases -- 1 Introduction -- 2 Related Work -- 3 The Proposed Algorithms -- 3.1 Random Sampling in B+Tree of Height Three -- 3.2 Random Sampling in B+Tree of Height Four -- 3.3 Generalization to Any B+Tree Height -- 4 Analysis -- 5 Simulation Study -- 5.1 Experiments Framework -- 5.2 Experiments Setup -- 5.3 Implementation Details -- 5.4 Results -- 6 Summary and Future Work -- References -- SQL-to-Schema Enhances Schema Linking in Text-to-SQL -- 1 Introduction -- 2 Related Work -- 2.1 Customized Machine Learning Fine-Tuned Methods -- 2.2 Stimulating General LLM with Prompting -- 3 Methodology -- 3.1 Evaluation Metrics -- 3.2 Introduction to Each Module -- 4 Experiments and Analysis -- 4.1 Experiment One -- 4.2 Experiment Two -- 4.3 Experiment Three -- 5 Conclusion -- References -- Efficient Algorithms for Top-k Stabbing Queries on Weighted Interval Data -- 1 Introduction -- 2 Preliminary -- 3 Algorithm Based on Interval Forest -- 3.1 Data Structure and Construction -- 3.2 Query Processing Algorithm -- 4 Algorithm Based on a Variant of Segment Tree -- 4.1 Variant of Segment Tree and Its Construction -- 4.2 Query Processing Algorithm -- 5 Conclusion -- References -- A Hierarchical Storage Mechanism for Hot and Cold Data Based on Temperature Model. 1 Introduction -- 2 Related Work -- 3 System Architecture -- 3.1 Data Temperature Model -- 3.2 Data Hierarchical Storage Mechanism -- 4 Experimentation and Analysis -- 4.1 Experimental Environment and Configuration -- 4.2 Experiment on Local Hot and Cold Data Migration Management -- 4.3 Experiment on Local and Remote Data Migration Management -- 5 Conclusion -- References -- Machine Learning and Large Language Models -- A Pre-trained Knowledge Tracing Model with Limited Data -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Transformer-Based Knowledge Tracing Model -- 3.2 BERT-Based Knowledge Tracing Model -- 4 Experiments -- 4.1 Datasets -- 4.2 Experimental Setup -- 4.3 Experiment Results and Analysis -- 5 Conclusions and Future Work -- References -- Chorus: More Efficient Machine Learning on Serverless Platform -- 1 Introduction -- 2 Background and Motivation -- 3 Lambda Synchronous Parallel (LSP) Model -- 4 Buffering in Parameter Server Model -- 5 Design of Chorus -- 5.1 Architecture Overview -- 6 Evaluation -- 6.1 Methodology -- 6.2 Lambda Synchronous Parallel (LSP) Model -- 6.3 Buffering System -- 6.4 Comparison -- 7 Conclusion -- References -- Evaluating Performance of LLaMA2 Large Language Model Enhanced by QLoRA Fine-Tuning for English Grammatical Error Correction -- 1 Introduction -- 2 Related Work -- 2.1 Grammar Error Correction -- 2.2 LLaMA2 Large Language Model -- 3 Methodology -- 3.1 Data Preparation -- 3.2 Prompts and Learning Strategies -- 3.3 Parameter Efficient Fine-Tuning via QLoRA -- 4 Experiments -- 4.1 Text Generation Settings -- 4.2 Parameter Settings of Training -- 4.3 Experimental Results -- 4.4 Error Type Analysis -- 4.5 Performance Evaluation of Open Source Language Tools -- 5 Conclusion -- References -- A Label Embedding Algorithm Based on Maximizing Normalized Cross-Covariance Operator -- 1 Introduction. 2 Preliminaries -- 3 The Proposed Method -- 4 Experiments -- 4.1 Benchmark Data Sets and Evaluation Metrics -- 4.2 Compared Methods and Experimental Settings -- 4.3 Performance Evaluation and Analysis -- 5 Conclusion -- References -- Analyzing the Efficacy of Large Language Models: A Comparative Study -- 1 Introduction -- 2 Literature Review -- 3 Datasets and Preprocessing -- 3.1 Dataset Construction by Question-Answer Pair Generation -- 3.2 Fine-Tuning the LLM -- 3.3 Document Parsing and Text Comprehension -- 4 Methodology -- 4.1 Integrated Evaluation: BLEU, ROUGE, and Cosine Similarity -- 4.2 Accuracy Assessment Through Z-Score Outlier Detection -- 5 Observations and Results -- 5.1 Classification of Errors -- 5.2 Comparison of Performance of Our Framework -- 6 Conclusion and Future Directions -- References -- Leveraging Large Language Models for Flexible and Robust Table-to-Text Generation -- 1 Introduction -- 2 Related Work -- 3 Methods and Experiment Settings -- 4 Experiments Results -- 5 Conclusion -- References -- Recommender Systems and Personalization -- Collaborative Filtering for the Imputation of Patient Reported Outcomes -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 MDASI-HN Data -- 3.2 Collaborative Filtering (CF) for MDASI-HN -- 4 Evaluation -- 4.1 Evaluation Metrics: -- 5 Experimental Results -- 5.1 Experimental Setup -- 5.2 Data Statistics -- 5.3 CF Techniques Comparison -- 5.4 Effect of k on CF-SYM-PCC Imputation -- 5.5 Comparing CF-SYM-PCC Against Other Methods -- 5.6 Comparing CF-SYM-PCC and LI Techniques Per Symptom -- 5.7 PCC Correlation Symptom Clusters -- 6 Conclusion -- References -- Category-Aware Sequential Recommendation with Time Intervals of Purchases -- 1 Introduction -- 2 Method -- 2.1 Problem Setup -- 2.2 Category and Time Interval Aware Sequence Recommendation -- 2.3 Framework of the Dual Model. 3 Performance Evaluation. |
| Record Nr. | UNINA-9910881098903321 |
|
Strauss Christine
|
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| Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XXVIII, 825 p. 205 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-46227-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Practical and real-world studies of machine learning, knowledge discovery, data mining -- Innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting -- Recent advances at the frontier of machine learning and data mining with other disciplines. . |
| Record Nr. | UNISA-996466244703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken
| Machine Learning and Knowledge Discovery in Databases [[electronic resource] ] : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XXXVI, 817 p. 231 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-46128-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Practical and real-world studies of machine learning,knowledge discovery, data mining -- Innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting -- Recent advances at the frontier of machine learning and data mining with other disciplines. |
| Record Nr. | UNISA-996465981903316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken
| Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part II / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XXVIII, 825 p. 205 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-46227-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Practical and real-world studies of machine learning, knowledge discovery, data mining -- Innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting -- Recent advances at the frontier of machine learning and data mining with other disciplines. . |
| Record Nr. | UNINA-9910484632103321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken
| Machine Learning and Knowledge Discovery in Databases : European Conference, ECML PKDD 2016, Riva del Garda, Italy, September 19-23, 2016, Proceedings, Part I / / edited by Paolo Frasconi, Niels Landwehr, Giuseppe Manco, Jilles Vreeken |
| Edizione | [1st ed. 2016.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 |
| Descrizione fisica | 1 online resource (XXXVI, 817 p. 231 illus.) |
| Disciplina | 006.31 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Artificial intelligence Pattern recognition Information storage and retrieval Database management Application software Data Mining and Knowledge Discovery Artificial Intelligence Pattern Recognition Information Storage and Retrieval Database Management Information Systems Applications (incl. Internet) |
| ISBN | 3-319-46128-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Practical and real-world studies of machine learning,knowledge discovery, data mining -- Innovative prototype implementations or mature systems that use machine learning techniques and knowledge discovery processes in a real setting -- Recent advances at the frontier of machine learning and data mining with other disciplines. |
| Record Nr. | UNINA-9910484032503321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
New Frontiers in Mining Complex Patterns [[electronic resource] ] : 8th International Workshop, NFMCP 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers / / edited by Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew Ras
| New Frontiers in Mining Complex Patterns [[electronic resource] ] : 8th International Workshop, NFMCP 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers / / edited by Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew Ras |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xii, 155 pages) : illustrations |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Computer communication systems Architecture, Computer Application software Education—Data processing Artificial Intelligence Data Mining and Knowledge Discovery Computer Communication Networks Computer System Implementation Computer Applications Computers and Education |
| ISBN | 3-030-48861-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Framework for Pattern Mining and Anomaly Detection in Multi-Dimensional Time Series and Event Logs -- A Heuristic Approach for Sensitive Pattern Hiding with Improved Data Quality -- Interpretable Survival Gradient Boosting Models with Bagged Trees Base Learners -- Neural Hybrid Recommender: Recommendation Needs Collaboration -- Discovering Discriminative Nodes for Classification with Deep Graph Convolutional Methods -- Soft Voting Windowing Ensembles for Learning from Partially Labelled Streams -- Disentangling Aspect and Opinion Words in Sentiment Analysis Using Lifelong PU Learning -- Customer Purchase Behavior Prediction in E-commerce: A Conceptual Framework and Research Agenda -- Hough Transform as a Tool for the Classification of Vehicle Speed Changes in on-road Audio Recordings. |
| Record Nr. | UNISA-996418318703316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
New Frontiers in Mining Complex Patterns : 8th International Workshop, NFMCP 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers / / edited by Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew Ras
| New Frontiers in Mining Complex Patterns : 8th International Workshop, NFMCP 2019, Held in Conjunction with ECML-PKDD 2019, Würzburg, Germany, September 16, 2019, Revised Selected Papers / / edited by Michelangelo Ceci, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew Ras |
| Edizione | [1st ed. 2020.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
| Descrizione fisica | 1 online resource (xii, 155 pages) : illustrations |
| Disciplina |
006.3
006.312 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Artificial intelligence
Data mining Computer networks Computer systems Application software Education—Data processing Artificial Intelligence Data Mining and Knowledge Discovery Computer Communication Networks Computer System Implementation Computer and Information Systems Applications Computers and Education |
| ISBN | 3-030-48861-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A Framework for Pattern Mining and Anomaly Detection in Multi-Dimensional Time Series and Event Logs -- A Heuristic Approach for Sensitive Pattern Hiding with Improved Data Quality -- Interpretable Survival Gradient Boosting Models with Bagged Trees Base Learners -- Neural Hybrid Recommender: Recommendation Needs Collaboration -- Discovering Discriminative Nodes for Classification with Deep Graph Convolutional Methods -- Soft Voting Windowing Ensembles for Learning from Partially Labelled Streams -- Disentangling Aspect and Opinion Words in Sentiment Analysis Using Lifelong PU Learning -- Customer Purchase Behavior Prediction in E-commerce: A Conceptual Framework and Research Agenda -- Hough Transform as a Tool for the Classification of Vehicle Speed Changes in on-road Audio Recordings. |
| Record Nr. | UNINA-9910409664803321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
New Frontiers in Mining Complex Patterns [[electronic resource] ] : 6th International Workshop, NFMCP 2017, Held in Conjunction with ECML-PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Revised Selected Papers / / edited by Annalisa Appice, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras
| New Frontiers in Mining Complex Patterns [[electronic resource] ] : 6th International Workshop, NFMCP 2017, Held in Conjunction with ECML-PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Revised Selected Papers / / edited by Annalisa Appice, Corrado Loglisci, Giuseppe Manco, Elio Masciari, Zbigniew W. Ras |
| Edizione | [1st ed. 2018.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
| Descrizione fisica | 1 online resource (XII, 197 p. 57 illus.) |
| Disciplina | 006.3 |
| Collana | Lecture Notes in Artificial Intelligence |
| Soggetto topico |
Data mining
Arithmetic and logic units, Computer Application software Artificial intelligence Data Mining and Knowledge Discovery Arithmetic and Logic Structures Computer Appl. in Social and Behavioral Sciences Artificial Intelligence |
| ISBN | 3-319-78680-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Learning Association Rules for Pharmacogenomic Studies -- Segment-Removal Based Stuttered Speech Remediation -- Identifying lncRNA-disease Relationships via Heterogeneous Clustering -- Density Estimators for Positive-Unlabeled Learning -- Combinatorial Optimization Algorithms to Mine a Sub-Matrix of Maximal Sum -- A Scaled-Correlation Based Approach for Defining and analyzing functional networks -- Complex Localization in the Multiple Instance Learning Context -- Integrating a Framework for Discovering Alternative App Stores in a Mobile App Monitoring Platform -- Usefulness of Unsupervised Ensemble Learning Methods for Time Series Forecasting of Aggregated or Clustered Load -- Phenotype Prediction with Semi-supervised Classification Trees -- Structuring the Output Space in Multi-label Classification by Using Feature Ranking -- Infinite Mixtures of Markov Chains -- Community-based Semantic Subgroup Discovery. |
| Record Nr. | UNISA-996465525603316 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
