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Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings / / edited by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl



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Titolo: Machine Learning and Knowledge Extraction : First IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 – September 1, 2017, Proceedings / / edited by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017
Edizione: 1st ed. 2017.
Descrizione fisica: 1 online resource (XV, 376 p. 129 illus.)
Disciplina: 004
Soggetto topico: Application software
Artificial intelligence
Coding theory
Information theory
Computer networks
Data protection
Computers and civilization
Computer and Information Systems Applications
Artificial Intelligence
Coding and Information Theory
Computer Communication Networks
Data and Information Security
Computers and Society
Persona (resp. second.): HolzingerAndreas
KiesebergPeter
TjoaA Min
WeipplEdgar
Nota di contenuto: Intro -- Preface -- Organization -- Contents -- MAKE Topology -- On Distance Mapping from non-Euclidean Spaces to Euclidean Spaces -- 1 Introduction -- 2 Notations -- 3 Distances over non-Euclidean Spaces -- 4 Mapping Solution -- 5 Algorithm of Distance Mapping -- 5.1 First Case -- 5.2 Second Case -- 6 Using ELM to Learn the Functional Distribution -- 7 Implementation Improvement -- 8 Experimental Results -- 9 Conclusion -- References -- Some Remarks on the Algebraic Properties of Group Invariant Operators in Persistent Homology -- 1 Introduction -- 2 Our Mathematical Model -- 3 Some New Results on Group Invariant Non-expansive Operators -- 4 Conclusions -- References -- Decentralized Computation of Homology in Wireless Sensor Networks Using Spanning Trees -- 1 Introduction -- 2 Homological Coverage Criteria -- 3 Decentralized Computation of Homology -- 3.1 Network Segmentation and Merging -- 3.2 Computing Betti Numbers -- 3.3 Merging Within a Spanning Tree -- 3.4 Merging Multiple Segments -- 3.5 Partial Merging -- 4 Results -- 5 Conclusions -- References -- Detecting and Ranking API Usage Pattern in Large Source Code Repository: A LFM Based Approach -- 1 Introduction -- 2 Related Work -- 3 LFM-OUPD: An Approach for Proper API Usage Pattern Recommendation -- 3.1 API Usage Pattern -- 3.2 Method Call Sequence Graph Constructor -- 3.3 API Usage Pattern Detector -- 3.4 Candidate API Usage Recommender -- 3.5 Candidate Code Examples Recommender -- 4 Case Study -- 4.1 Setup -- 4.2 CacheBuilder Method Case -- 5 Conclusion -- References -- MAKE Smart Factor -- Towards a Framework for Assistance Systems to Support Work Processes in Smart Factories -- Abstract -- 1 Introduction and Motivation -- 2 Methodological Considerations -- 3 Framework -- 4 Framework Application -- 4.1 Intelligent Worker Assistance (Büttner et al. 2017).
4.2 TeleAdvisor (Gurevich et al. 2012) -- 4.3 Smart-Glasses-Based Service Support System (Niemöller et al. 2017) -- 5 Conclusion and Outlook -- References -- Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Reduction -- 1 Introduction and Motivation -- 2 Related Work -- 2.1 Assistive Systems for Error-Handling -- 2.2 Alarm Flood Reduction -- 2.3 Interactive Machine Learning (iML) -- 3 Method -- 4 Concept -- 4.1 Alarm Flood Reduction -- 4.2 Adaptive and Responsive User Interface -- 5 Prototype -- 5.1 Architecture -- 5.2 Machine Learning Algorithms -- 5.3 User Interface -- 6 Discussion, Conclusion and Outlook -- References -- Online Self-disclosure: From Users' Regrets to Instructional Awareness -- 1 Introduction -- 2 Related Work -- 2.1 Self-disclosure in the Privacy Landscape -- 2.2 Preventative Technologies -- 3 Theoretical Background -- 3.1 Self-disclosure Privacy Concerns -- 3.2 Regrets in SNSs -- 3.3 Instructional Awareness -- 4 Privacy Heuristics Derivation (PHeDer) -- 4.1 Conceptual Model -- 4.2 Method -- 5 Privacy Heuristics Evaluation in IAS -- 6 Discussion and Future Work -- 7 Conclusion -- References -- MAKE Privacy -- Decision Tree Rule Induction for Detecting Covert Timing Channels in TCP/IP Traffic -- 1 Introduction -- 2 Related Work -- 3 DAT Detector -- 4 Implemented Timing Techniques -- 5 Experiments -- 6 Results -- 6.1 Rule Extraction Experiments -- 6.2 DAT Testing After Generalization -- 7 Conclusion -- References -- Practical Estimation of Mutual Information on Non-Euclidean Spaces -- 1 Introduction -- 2 A Short Primer on Anonymization Techniques -- 2.1 k-anonymity -- 2.2 Differential Privacy -- 3 Notations -- 3.1 Distances over Non-Euclidean Spaces -- 4 Mutual Information for Usability Quantification -- 4.1 Estimating Mutual Information -- 5 Experimental Results.
5.1 GPS Routes (Timestamped Data) -- 5.2 Convergence of the MI Estimators -- 5.3 k-anonymity Effects on the Trajectory Datasets -- 5.4 Differential Privacy Effects on the Trajectory Datasets -- 6 Conclusion -- References -- IntelliAV: Toward the Feasibility of Building Intelligent Anti-malware on Android Devices -- 1 Introduction -- 1.1 On-Device Advanced Security -- 1.2 Contribution -- 2 System Design -- 2.1 Feature Extraction -- 2.2 Model Construction -- 2.3 On-Device Testing -- 3 Experimental Analysis -- 3.1 Experimental Setup -- 3.2 Results -- 3.3 IntelliAV Overhead on Device -- 4 Limitations -- 5 Related Works -- 6 Conclusions and Future Work -- References -- DO NOT DISTURB? Classifier Behavior on Perturbed Datasets -- 1 Introduction and Related Work -- 2 K-Anonymity and Information Loss -- 3 Experiments -- 3.1 Data -- 3.2 Anonymization Algorithm -- 3.3 Dataset Creation -- 4 Results and Discussion -- 4.1 Perturbed Datasets - Selective Deletion -- 4.2 Anonymized Datasets -- 4.3 ``Outliers'' Removed -- 4.4 Anonymization on Outliers Removed -- 5 Open Problems/Future Challenges -- 6 Conclusion -- References -- A Short-Term Forecast Approach of Public Buildings' Power Demands upon Multi-source Data -- Abstract -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Grey Correlation Analysis -- 3.2 Probability Graph Model -- 4 Case Study and Result -- 4.1 Data Preparation -- 4.2 Influence Factors -- 4.2.1 Scatter Diagram -- 4.2.2 Remove Noisy Factors -- 4.3 Prediction -- 5 Error Analysis and Discussion -- 6 Conclusion -- Acknowledgements -- References -- MAKE VIS -- On the Challenges and Opportunities in Visualization for Machine Learning and Knowledge Extraction: A Research Agenda -- 1 Introduction -- 2 A Few Examples of Visualization and Machine Learning Integration -- 3 Challenges and Opportunities for Research.
4 A Potential Road-Map for Bridging the Communities -- 5 Conclusion -- References -- Quantitative Externalization of Visual Data Analysis Results Using Local Regression Models -- 1 Introduction -- 2 Related Work -- 3 Data Description and Problem Statement -- 4 Interactive Regression Modeling -- 4.1 Linear Regression Models -- 4.2 Interactive Modeling -- 5 Case Study -- 6 Discussion, Conclusion, and Future Work -- References -- Analysis of Online User Behaviour for Art and Culture Events -- 1 Introduction -- 1.1 Context -- 1.2 Problem Statement -- 1.3 Proposed Solution -- 1.4 Structure of the Paper -- 2 Related Work -- 3 Approach -- 3.1 Data Extraction -- 3.2 Data Preprocessing -- 3.3 Data Analysis Overview -- 3.4 Topic Modeling -- 3.5 Clustering -- 3.6 Prediction of User Interest -- 4 Implementation -- 5 Case Study -- 6 Results and Discussion -- 6.1 User Clustering -- 6.2 Applying Topic Modeling -- 6.3 Cluster Hierarchy -- 6.4 Cluster Labeling/User Profiling -- 6.5 Demographic Analysis - Language -- 6.6 Demographic Analysis - Gender -- 6.7 Prediction of Interests of New Users -- 7 Conclusion and Future Work -- References -- On Joint Representation Learning of Network Structure and Document Content -- 1 Introduction -- 2 Background -- 2.1 Word Embeddings -- 2.2 Document Embeddings -- 2.3 Graph Embeddings -- 3 Combining Link and Text Information -- 3.1 Paragraph Vector on Graphs -- 3.2 Fusing Link and Text Information -- 4 Related Work -- 4.1 Paper2Vec -- 4.2 TADW -- 5 Evaluation -- 6 Summary and Future Work -- References -- MAKE AAL -- Ambient Assisted Living Technologies from the Perspectives of Older People and Professionals -- 1 Introduction -- 2 Methodology -- 2.1 Planning -- 2.2 Focus Group and Sampling -- 2.3 Data Collection -- 2.4 Ethics -- 2.5 Data Analysis -- 3 Findings and Discussions -- 3.1 Daily Living.
3.2 Social Engagement and Physical Activities -- 3.3 Technology -- 3.4 Suggestions/Recommendations -- 4 Conclusion -- References -- Human Activity Recognition Using Recurrent Neural Networks -- 1 Introduction -- 2 Related Work -- 3 LSTM Model -- 4 Experiments -- 4.1 Dataset -- 4.2 Results -- 5 Discussion -- 6 Future Work -- References -- Modeling Golf Player Skill Using Machine Learning -- Abstract -- 1 Introduction -- 2 Background -- 3 Related Work -- 4 Method -- 4.1 Data Collection -- 4.2 Preprocessing -- 4.3 Experiments -- 4.4 Model Interpretation -- 5 Results -- 5.1 Basic Statistics -- 5.2 Predictive Performance -- 5.3 Interpretation of Models -- 6 Discussion and Conclusions -- References -- Predicting Chronic Heart Failure Using Diagnoses Graphs -- 1 Introduction -- 2 Data Description -- 3 Building a Representational Predictive Model -- 4 Predicting Heart Failure for an Unseen Patient -- 5 Results -- 6 Discussion -- 7 Conclusion -- References -- MAKE Semantics -- A Declarative Semantics for P2P Systems -- 1 Introduction -- 2 Background -- 3 P2P Systems: Syntax and Semantics -- 3.1 Syntax -- 3.2 Semantics -- 4 A More General Framework -- 5 Query Answers and Complexity -- 6 Related Work -- 7 Conclusion -- References -- Improving Language-Dependent Named Entity Detection -- Abstract -- 1 Introduction -- 2 State of the Art in Entity Detection (Spotting) -- 3 TOMO Approach to Optimize Spotter for the German Language -- 4 Evaluation Measures and Datasets -- 4.1 Measures and Benchmarking -- 4.2 Dataset -- 5 Experiments and Results -- 6 Conclusions and Future Work -- Acknowledgements -- References -- Towards the Automatic Detection of Nutritional Incompatibilities Based on Recipe Titles -- 1 Introduction -- 2 State of the Art -- 3 Experimental Setup -- 3.1 Problem Statement -- 3.2 Nutritional Incompatibility Representation -- 3.3 Corpus.
3.4 Knowledge Resource.
Sommario/riassunto: This book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017. The 24 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers deal with fundamental questions and theoretical aspects and cover a wide range of topics in the field of machine learning and knowledge extraction. They are organized in the following topical sections: MAKE topology; MAKE smart factory; MAKE privacy; MAKE VIS; MAKE AAL; and MAKE semantics.
Titolo autorizzato: Machine Learning and Knowledge Extraction  Visualizza cluster
ISBN: 3-319-66808-0
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910483828003321
Lo trovi qui: Univ. Federico II
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Serie: Information Systems and Applications, incl. Internet/Web, and HCI, . 2946-1642 ; ; 10410