Note: Intro -- Preface -- Organization -- Contents -- Knowledge Engineering, Knowledge Representation and Probabilistic Reasoning -- Towards an Integration of Workflows and Clinical Guidelines: A Case Study -- Abstract -- 1 Introduction -- 2 Comparing WFs and CPGs: A Case Study -- 2.1 Workflow for the Vinorelbine Treatment (in Day Hospital) -- 2.2 Guideline for the Vinorelbine Treatment of Advanced Non-small Cell Lung Cancer -- 2.3 Comparisons -- 3 Towards an Integrated Architecture -- 4 Ongoing and Future Work -- 4.1 Open Issues -- 5 Conclusion -- References -- Anomalies Detection in the Behavior of Processes Using the Sensor Validation Theory -- 1 Introduction -- 2 Anomaly Detection -- 3 Sensor Validation Theory -- 4 Proposed Model for Anomaly Detection in the Behavior -- 5 Experiments and Results -- 6 Conclusions and Future Work -- References -- Explanatory Relations Revisited: Links with Credibility-Limited Revision -- 1 Introduction -- 2 Preliminaries -- 2.1 Credibility-Limited Revision -- 3 An Abstract Approach for Abduction -- 4 Credibility Limited Explanatory Relations -- 4.1 Ordered Explanatory Relations -- 5 Final Remarks -- References -- Semantic Enrichment of Web Service Operations -- Abstract -- 1 Introduction -- 2 Web Service Parsing and Extraction -- 3 Web Service Ontology Model -- 4 Web Service Similarity Calculation -- 4.1 Similarity Decision -- 5 Evaluation -- 6 Related Work -- 7 Conclusions -- References -- Agent Technology and Multi-agent Systems -- The ICARO Goal Driven Agent Pattern -- Abstract -- 1 Introduction -- 2 Overview of the ICARO Framework -- 3 The Goal Driven Agent Pattern -- 4 Example of Development of a Goal Driven Agent -- 5 Conclusions -- Acknowledgements -- References -- A Study for Self-adapting Urban Traffic Control -- 1 Introduction -- 2 The Netlogo City Model -- 3 Self-organizing Traffic Lights (SOTL). , 4 History-Based SOTL (HB-SOTL) -- 5 History-Based SOTL Results -- 6 Adaptability to Changing Traffic Conditions -- 7 Reducing the Sensor Density -- 8 Self-organizing UTC with Communication -- 9 Conclusions -- References -- Planning and Scheduling -- A Constraint-Based Approach for the Conciliation of Clinical Guidelines -- 1 Introduction -- 2 GLARE and Comorbidities: Overview of the Approach -- 3 CIG Conciliation -- 3.1 The TO CSP Function -- 3.2 CSP Propagation -- 3.3 The TO CIG Function -- 3.4 Case Study -- 4 Conclusions -- References -- Intelligence Amplification Framework for Enhancing Scheduling Processes -- Abstract -- 1 Introduction -- 2 Problem Background -- 2.1 Human-in-the-Loop and Intelligent Systems -- 2.2 Synchromodal Logistics -- 3 Solution Design -- 3.1 Symbiotic Man-Machine Relationship -- 3.2 Environment -- 3.3 Framework Design for Enhanced Scheduling in Synchromodal Logistics -- 3.4 Implementing Intelligent Agents -- 4 Testing and Validation -- 5 Conclusion and Future Work -- References -- A Column Generation Approach for Solving a Green Bi-objective Inventory Routing Problem -- Abstract -- 1 Introduction -- 2 Overview of Related Literature -- 2.1 Inventory Routing Problem (IRP) -- 2.2 Multi-objective IRP -- 2.3 Green IRP -- 2.4 Classification of IRP Models and Green IRP -- 3 Problem Definition -- 3.1 Mathematical Model -- 4 Solution Approach -- 4.1 Column Generation Formulation -- 4.2 Multi-objective Algorithm -- 5 Computational Experiments and Results -- 6 Conclusions -- Acknowledgments -- References -- Natural Language Processing -- Enhancing Semi-supevised Text Classification Using Document Summaries -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 3.1 Text Summarization Module -- 3.2 Instance Selection Module -- 3.3 Classification Module -- 4 Experimental Results -- 4.1 Data Set -- 4.2 Method Configuration. , 4.3 Baseline Definition -- 4.4 Evaluation Metrics -- 4.5 Results -- 4.6 Discussion -- 5 Conclusions -- References -- A Comparison Between Two Spanish Sentiment Lexicons in the Twitter Sentiment Analysis Task -- 1 Introduction -- 2 Resources -- 3 Method -- 4 Results and Discussion -- 4.1 Analysis of Results -- 4.2 Corpus Analysis -- 5 Conclusions and Future Work -- References -- Is This a Joke? Detecting Humor in Spanish Tweets -- 1 Introduction -- 2 Computational Humor -- 2.1 Humor Detection -- 2.2 State of the Art -- 3 Proposal -- 3.1 Corpus -- 3.2 Classifier -- 4 Experimental Evaluation -- 5 Conclusions -- References -- Evaluating Topic-Based Representations for Author Profiling in Social Media -- 1 Introduction -- 2 Related Work -- 3 Features -- 3.1 LSA -- 3.2 LIWC -- 3.3 Corpora -- 4 Experimental Settings -- 5 Results -- 5.1 Age Results -- 5.2 Gender Results -- 6 Conclusions -- References -- Using Robustness to Learn to Order Semantic Properties in Referring Expression Generation -- 1 Introduction -- 2 Related Work -- 3 Data -- 4 Experimental Setup -- 4.1 Metrics -- 4.2 A Genetic Algorithm Set-Up for Person Priorities Ontology -- 5 Results -- 6 Discussion -- 7 Conclusions -- References -- Conditional Random Fields for Spanish Named Entity Recognition Using Unsupervised Features -- 1 Introduction -- 2 Related Work -- 2.1 Spanish NER -- 2.2 Unsupervised Word Features -- 3 Unsupervised Word Features for Spanish NER -- 3.1 Brown Clustering -- 3.2 Clustering Embeddings -- 3.3 Binarized Embeddings -- 3.4 Distributional Prototypes -- 3.5 Collocations -- 4 Experiments and Discussion -- 4.1 NER Model -- 4.2 Baseline Features -- 4.3 CoNLL 2002 Spanish Corpus -- 4.4 Unsupervised Word Features -- 4.5 Results -- 4.6 Discussion -- 5 Conclusions -- References -- Machine Learning -- Detection of Fraud Symptoms in the Retail Industry -- 1 Introduction. , 2 Data Mining in the Detection of Fraud Symptoms -- 2.1 Supervised vs Unsupervised Learning -- 2.2 Outlier Detection -- 3 Outliers Detection on Returned Items in Stores -- 3.1 Univariate Analysis -- 3.2 Bivariate Analysis -- 3.3 Multivariate Analysis -- 4 Conclusions and Future Work -- References -- A Machine Learning Model for Occupancy Rates and Demand Forecasting in the Hospitality Industry -- 1 Introduction -- 2 Machine Learning Algorithms -- 2.1 Ridge Regression -- 2.2 Kernel Ridge Regression -- 2.3 Multilayer Perceptron -- 2.4 Radial Basis Function Networks -- 3 Model Development -- 3.1 Dataset Construction -- 3.2 Training and Validation -- 3.3 Test -- 4 Conclusion -- References -- A Machine Learning Model for Triage in Lean Pediatric Emergency Departments -- 1 Introduction -- 2 Machine Learning Algorithms -- 2.1 Logistic Regression -- 2.2 Support Vector Machine -- 2.3 Multilayer Perceptron -- 3 Model Development -- 3.1 Dataset Construction -- 3.2 Training and Validation -- 3.3 Test -- 4 Conclusion -- References -- An Empirical Validation of Learning Schemes Using an Automated Genetic Defect Prediction Framework -- 1 Introduction -- 2 Research Questions -- 3 Related Work -- 4 Proposed Framework -- 4.1 Learning Schemes Generator -- 4.2 Defect Prediction -- 5 Genetic Configuration -- 5.1 Chromosome -- 5.2 Fitness Function -- 5.3 Operators -- 6 Empirical Study -- 6.1 Data Sets -- 6.2 Learning Schemes -- 6.3 Experimental Design -- 7 Results and Analysis -- 8 Statistical Analysis -- 9 Threats to Validity -- 10 Conclusions and Future Work -- References -- Machine Learning Approaches to Estimate Simulated Cardiac Ejection Fraction from Electrical Impedance Tomography -- 1 Introduction -- 2 Materials and Methods -- 2.1 Simulated Dataset -- 2.2 Regression Models -- 2.3 Parameter Settings Using Cross-Validation -- 3 Results and Discussion. , 4 Conclusions -- References -- Machine Learning Models for Early Dengue Severity Prediction -- 1 Introduction -- 2 Methods and Materials -- 2.1 Participants -- 2.2 Dataset -- 2.3 Learning Models -- 3 Results -- 3.1 Training and Validation -- 3.2 Test -- 4 Discussion -- 5 Conclusions -- References -- Early Prediction of Severe Maternal Morbidity Using Machine Learning Techniques -- 1 Introduction -- 2 Related Work -- 3 Methods and Materials -- 3.1 Participants -- 3.2 Data Set -- 3.3 Statistical Data Analysis -- 3.4 Learning Models -- 4 Results -- 4.1 Statistical Analysis -- 4.2 Training -- 5 Conclusions -- References -- Big Data, Knowledge Discovery and Data Mining -- Collaborative Filtering with Semantic Neighbour Discovery -- 1 Introduction -- 2 Semantically Enriched Collaborative Recommendation -- 2.1 Collaborative Filtering -- 2.2 Semantic Enrichment -- 3 UbCF with Semantic Neighbour Discovery -- 4 Tests and Results -- 4.1 Data Set -- 4.2 Evaluation Metrics -- 4.3 Results -- 5 Conclusions -- References -- Distributed and Parallel Algorithm for Computing Betweenness Centrality -- 1 Introduction -- 2 Definitions and Notations -- 3 Previous Work -- 3.1 Sequential Algorithms -- 3.2 Parallel and Distributed Algorithms -- 4 Our Proposal -- 4.1 Modification for Sparse Networks -- 5 Experiments -- 6 Conclusions and Future Work -- References -- Principal Curves and Surfaces to Interval Valued Variables -- 1 Symbolic Data -- 2 Self-Consistency of a Random Vector -- 3 Principal Surface -- 4 The Principal Curves and Surfaces to Interval Valued Variables -- 5 Experimental Evaluation -- 6 Conclusion -- References -- In Defense of Online Kmeans for Prototype Generation and Instance Reduction -- 1 Introduction -- 2 Related Work -- 2.1 Batch Learning Based Methods for IR -- 2.2 Incremental/Online Learning -- 3 Online K-Means for Instance Reduction. , 4 Experimentation.