LEADER 13013nam 22008655 450 001 9910483828003321 005 20250704091743.0 010 $a3-319-66808-0 024 7 $a10.1007/978-3-319-66808-6 035 $a(CKB)3710000001631290 035 $a(DE-He213)978-3-319-66808-6 035 $a(MiAaPQ)EBC6283074 035 $a(MiAaPQ)EBC5590862 035 $a(Au-PeEL)EBL5590862 035 $a(OCoLC)1005114370 035 $a(PPN)203850483 035 $a(EXLCZ)993710000001631290 100 $a20170823d2017 u| 0 101 0 $aeng 135 $aurnn#008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning and Knowledge Extraction $eFirst IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference, CD-MAKE 2017, Reggio, Italy, August 29 ? September 1, 2017, Proceedings /$fedited by Andreas Holzinger, Peter Kieseberg, A Min Tjoa, Edgar Weippl 205 $a1st ed. 2017. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017. 215 $a1 online resource (XV, 376 p. 129 illus.) 225 1 $aInformation Systems and Applications, incl. Internet/Web, and HCI,$x2946-1642 ;$v10410 311 08$a3-319-66807-2 327 $aIntro -- 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 (Bu?ttner et al. 2017). 327 $a4.2 TeleAdvisor (Gurevich et al. 2012) -- 4.3 Smart-Glasses-Based Service Support System (Niemo?ller 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. 327 $a5.1 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. 327 $a4 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. 327 $a3.2 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. 327 $a3.4 Knowledge Resource. 330 $aThis book constitutes the refereed proceedings of the IFIP TC 5, WG 8.4, 8.9, 12.9 International Cross-Domain Conference for Machine Learning and Knowledge Extraction, CD-MAKE 2017, held in Reggio, Italy, in August/September 2017. The 24 revised full papers presented were carefully reviewed and selected for inclusion in this volume. The papers deal with fundamental questions and theoretical aspects and cover a wide range of topics in the field of machine learning and knowledge extraction. They are organized in the following topical sections: MAKE topology; MAKE smart factory; MAKE privacy; MAKE VIS; MAKE AAL; and MAKE semantics. 410 0$aInformation Systems and Applications, incl. Internet/Web, and HCI,$x2946-1642 ;$v10410 606 $aApplication software 606 $aArtificial intelligence 606 $aCoding theory 606 $aInformation theory 606 $aComputer networks 606 $aData protection 606 $aComputers and civilization 606 $aComputer and Information Systems Applications 606 $aArtificial Intelligence 606 $aCoding and Information Theory 606 $aComputer Communication Networks 606 $aData and Information Security 606 $aComputers and Society 615 0$aApplication software. 615 0$aArtificial intelligence. 615 0$aCoding theory. 615 0$aInformation theory. 615 0$aComputer networks. 615 0$aData protection. 615 0$aComputers and civilization. 615 14$aComputer and Information Systems Applications. 615 24$aArtificial Intelligence. 615 24$aCoding and Information Theory. 615 24$aComputer Communication Networks. 615 24$aData and Information Security. 615 24$aComputers and Society. 676 $a004 702 $aHolzinger$b Andreas$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aKieseberg$b Peter$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aTjoa$b A Min$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aWeippl$b Edgar$4edt$4http://id.loc.gov/vocabulary/relators/edt 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910483828003321 996 $aMachine Learning and Knowledge Extraction$91896731 997 $aUNINA