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• Table of Contents Introduction to Markov Process Hidden Markov Models State Inference: Predicting the states Parameter Inference using Maximum Likelihood Parameter Inference using Bayesian Approach Time Series: Predicting Stock Prices Natural Language Processing: Teaching machines to talk 2D-HMM for Image Processing Reinforcement Learning: Teaching a robot to cross a maze.
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Unleash the power of unsupervised machine learning in Hidden Markov Models using TensorFlow, pgmpy, and hmmlearn Key Features Build a variety of Hidden Markov Models (HMM) Create and apply models to any sequence of data to analyze, predict, and extract valuable insights Use natural language processing (NLP) techniques and 2D-HMM model for image segmentation Book DescriptionHidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. The hands-on examples explored in the book help you simplify the process flow in machine learning by using Markov model concepts, thereby making it accessible to everyone. Once you've covered the basic concepts of Markov chains, you'll get insights into Markov processes, models, and types with the help of practical examples. After grasping these fundamentals, you'll move on to learning about the different algorithms used in inferences and applying them in state and parameter inference. In addition to this, you'll explore the Bayesian approach of inference and learn how to apply it in HMMs. In further chapters, you'll discover how to use HMMs in time series analysis and natural language processing (NLP) using Python. You'll also learn to apply HMM to image processing using 2D-HMM to segment images. Finally, you'll understand how to apply HMM for reinforcement learning (RL) with the help of Q-Learning, and use this technique for single-stock and multi-stock algorithmic trading. By the end of this book, you will have grasped how to build your own Markov and hidden Markov models on complex datasets in order to apply them to projects. What you will learn Explore a balance of both theoretical and practical aspects of HMM Implement HMMs using different datasets in Python using different packages Understand multiple inference algorithms and how to select the right algorithm to resolve your problems Develop a Bayesian approach to inference in HMMs Implement HMMs in finance, natural language processing (NLP), and image processing Determine the most likely sequence of hidden states in an HMM using the Viterbi algorithm Who this book is forHands-On Markov Models with Python is for you if you are a data analyst, data scientist, or machine learning developer and want to enhance your machine learning knowledge and skills. This book will also help you build your own hidden Markov models by applying them to any sequence of data. Basic knowledge of machine learning and the Python programming language is expected to get the most out of the book.
(source: Nielsen Book Data)

"The first book that provides a systematic and rigorous logical theory of causality"-- Provided by publisher.

"A collection of critical essays dealing with the social and ethical impacts of AI including issues of trust, reliability, and bias"-- Provided by publisher.

• Introduction.- Part 1:Background and Methodology.- Discrete Consensus Achievement in Artificial Systems.- Modular Design of Strategies for the Best-of-n Problem.- Part 2:Mathematical Modeling and Analysis.- Indirect Modulation of Majority-Based Decisions.- Direct Modulation of Voter-Based Decisions.- Direct Modulation of Majority-Based Decisions.- Part 3:Robot Experiments.- A Robot Experiment in Site Selection.- A Robot Experiment in Collective Perception.- Part 4:Discussion and Annexes.- Conclusions.- Background on Markov Chains.
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This book focuses on the design and analysis of collective decision-making strategies for the best-of-n problem. After providing a formalization of the structure of the best-of-n problem supported by a comprehensive survey of the swarm robotics literature, it introduces the functioning of a collective decision-making strategy and identifies a set of mechanisms that are essential for a strategy to solve the best-of-n problem. The best-of-n problem is an abstraction that captures the frequent requirement of a robot swarm to choose one option from of a finite set when optimizing benefits and costs. The book leverages the identification of these mechanisms to develop a modular and model-driven methodology to design collective decision-making strategies and to analyze their performance at different level of abstractions. Lastly, the author provides a series of case studies in which the proposed methodology is used to design different strategies, using robot experiments to show how the designed strategies can be ported to different application scenarios.
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• Local Perturbation Analysis Of The Stochastic Matrix Riccati Equation With Applications In Finance.- An Embedded Compact Scheme For Biharmonic Problems In Irregular Domains.- Ant Colony Optimization Algorithm For 1D Cutting Stock Problem.- 2D Optimal Cutting Problem.- Error Estimate In The Iterative Numerical Method For Two-Dimensional Nonlinear Hammerstein-Fredholm Fuzzy Functional Integral Equations.- Noise Removal And Feature Extraction Of 2D CT Radiographic Images.- Representation Of Civilians And Police Officers By Generalized Nets For Describing Software Agents In The Case Of Protest.- Comparison Of NDT Techniques For Elastic Modulus Determination Of Laminated Composites.- Integer Codes For Flash Memories.- On The Strong Asymptotics Of Rows Of The Pade Table.- Total Phosphorus Removal In Horizontal Subsurface Flow Constructed Wetlands: A Computational Investigation For The Optimal Adsorption Model.- Some Results Involving Euler-Type Integrals And Dilogarithm Values.- Nonlinear Evolution Equation For Propagation Of Waves In An Artery With An Aneurysm: An Exact Solution Obtained By The Modified Method Of Simplest Equation.- Modelling Of Light Mg And Al Based Alloys As "In Situ" Composites.- Asymptotic Study Of The Nonlinear Velocity Problem For The Oscillatory Non-Newtonian Flow In A Straight Channel.- Competition For Resources And Space Contributes To The Emergence Of Drug Resistance In Cancer.- Efficient Error Based Metrics For Fuzzy-Neural Network Performance Evaluation.- Box Model Of Migration In Channels Of Migration Networks.- Modified Coordinates In Dynamics Simulation Of Multibody Systems With Elastic Bodies.
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This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas, bringing together mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc. Further, the book presents the major tools used in Industrial Mathematics, which are based on mathematical models, and the corresponding computer codes, which are used to perform virtual experiments to obtain new data or to better understand previous experimental findings. The book gathers the peer-reviewed papers presented at the 11th Annual Meeting of the Bulgarian Section of SIAM (BGSIAM), from December 20 to 22, 2016 in Sofia, Bulgaria.
(source: Nielsen Book Data)

• 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 Inter
• section 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.
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This book constitutes the refereed proceedings of the 13th International Conference on Advanced Data Mining and Applications, ADMA 2017, held in Singapore in November 2017. The 20 full and 38 short papers presented in this volume were carefully reviewed and selected from 118 submissions. The papers were organized in topical sections named: database and distributed machine learning; recommender system; social network and social media; machine learning; classification and clustering methods; behavior modeling and user profiling; bioinformatics and medical data analysis; spatio-temporal data; natural language processing and text mining; data mining applications; applications; and demos. .
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• Information systems architecture.- Business process alignment.- User knowledge discovery.- Business process performance.- Big data exploration.- Process variability management.- Information systems transformation and evolution.- Business process modeling readability.- Business process adaption.- Data mining.- Process discovery.- Business process modeling notation.
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This book constitutes the refereed proceedings of the 29th International Conference on Advanced Information Systems Engineering, CAiSE 2017, held in Essen, Germany, in June 2017. The 37 papers presented together with 3 keynote papers in this volume were carefully reviewed and selected from 175 submissions. The papers are organized in topical sections on information systems architecture; business process alignment; user knowledge discovery; business process performance; big data exploration; process variability management; information systems transformation and evolution; business process modeling readability; business process adaption; data mining; process discovery; business process modeling notation.
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• Part I: From Machine Learning to Data Mining.- Analyzing Accident Prone Regions by Clustering.- Analyzing Life Insurance Data with Different Classification Techniques for Customers' Behavior Analysis.- Classification of Product Rating Using Data Mining Techniques.- MASS: a Semi-Supervised Multi-Label Classification Algorithm with Specific Feature.- Parallel Self-organizing Map Using Shared Virtual Memory Buffers.- Parametric Optimization of the Selected Classifiers in Binary Classification.- Prediction of Academic Performance During Adolescence Based on Socioeconomic, Psychological and Academic Factors.- A Super-Vector Deep Learning Coprocessor with High Performance-Power Ratio.- Part II: Big Data and Collaborative Decision Support Systems.- Bi-temporal Database Model for Legal Merger Transactions and Late-arriving Information Problem: the Case of Polish Merger Market.- Breathing Movement Analysis for Adjustment of Radiotherapy Planning.- Measuring Improvement in Access to Complete Data in Healthcare Collaborative Dabase Systems.- Rough Set Theory for Supporting Decision Making on Relevance in Browsing Multilingual Digital Resources.- The Social Influence on the Behavioral Intention to Use Mobile Electronic Medical Records.- Stock Prices Growth Pattern by the Emergency Demand After the Great East-Japan Earthquake.- Structure-Based Virtual Screening for Novel Modulators of Human Orexin 2 Receptor with Cloud Systems and Supercomputers.- Supply Chains of Cross-Border E-Commerce.- Towards Personalized Virtual Customer Experience.- Towards Big Management.- Part III: Computer Vision Analysis, Detection, Tracking and Recognition.- Combination of Collision Detection and Visibility Algorithms in Simulation of Effective Placement of Anti-Air Elements.- A Combination of Deep Learning and Hand-Designed Feature for Plant Identification based on Leaf and Flower Images.- An Efficient Defect Classification Algorithm for Ceramic Tiles.- Parking Assistant - Prediction of an Empty Parking Space in Time.- Recent Advances in the Field of Foreground Detection: An Overview.- Tracking of Bone Reparation Process with Using of Periosteal Callus Extraction based on Fuzzy C-Means Algorithm.- Part IV: Data-Intensive Text Processing.- Automatic Post-Editing of Kazakh Sentences Machine Translated from English.- Complex Technology of Machine Translation Resources Extension for the Kazakh Language.- Enhancing Latent Semantic Analysis by Embedding Tagging Algorithm in Retrieving Malay Text Documents.- Exploiting Distance Graph and Hidden Topic Models for Multi-label Text Classification.- Financial Reports and Financial News - An Information Content Gap Analysis.- The Great National Photocorpus of 20th-Century Vietnamese. Origins, assumptions and goals.- The Impact of User Sentiment Aroused by The-day-of-the-week on the Recommendation Effectiveness in Microblog.- Multi-Sentence Compression Using Word Graph and Integer Linear Programming.- A Performance Comparison of Feature Extraction Methods for Sentiment Analysis.- A Study of Plagiarism Checker System Based on Chinese Word Segmentation and SQL Intersection Operation Technique.- Text Summarization Based on Classification Using ANFIS.- Part V: Innovations in Web and Internet Technologies.- Analysis of Indoor Positioning Based on BLE.- A Fusion Technique of Schema and Syntax Rules for Validating Open Data.- Job Description Language for a Browser-Based Computing Platform - A Preliminary Report.- Measuring the Effectiveness of Knowledge Driven Web Applications.- Responsive Data Table Solution with New Scrolling Control Gesture for Better User Experience.- Part VI: New Methods and Applications in Software Engineering.- Adaptation of an ANN-Based Air Quality Forecasting Model to a New Application Area.- Checking Compliance of Program with SecureUML Model.- Generation of Test Data using Genetic Algorithm and Constraint Solver.- Investigating the Issues of using Agile Methods in Offshore Software Development in Sri Lanka.- A Method for Automated Test Cases Generation from UML Models with String ConstraintS.- Mobile Application for Calculation of Optimal Route Between Searched Points of Interest.- On Implementation of the Assumption Generation Method for Component-Based Software Verification.
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This book presents recent research in intelligent information and database systems. The carefully selected contributions were initially accepted for presentation as posters at the 9th Asian Conference on Intelligent Information and Database Systems (ACIIDS 2017) held from to 5 April 2017 in Kanazawa, Japan. While the contributions are of an advanced scientific level, several are accessible for non-expert readers. The book brings together 47 chapters divided into six main parts: * Part I. From Machine Learning to Data Mining.* Part II. Big Data and Collaborative Decision Support Systems, * Part III. Computer Vision Analysis, Detection, Tracking and Recognition, * Part IV. Data-Intensive Text Processing, * Part V. Innovations in Web and Internet Technologies, and* Part VI. New Methods and Applications in Information and Software Engineering. The book is an excellent resource for researchers and those working in algorithmics, artificial and computational intelligence, collaborative systems, decision management and support systems, natural language processing, image and text processing, Internet technologies, and information and software engineering, as well as for students interested in such research areas.
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• Constraints, planning, and optimization.- Data mining and machine learning.- Sensors, signal processing, and data fusion.- Recommender systems.- Decision support systems.- Knowledge representation and reasoning.- Navigation, control, and autonome agents.- Sentiment analysis and social media.- Games, computer vision, and animation.- Uncertainty management.- Graphical models: from theory to applications.- Anomaly detection.- Agronomy and artificial intelligence.- Applications of argumentation.- Intelligent systems in healthcare and mhealth for health outcomes.- Innovative applications of textual analysis based on AI.
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The two-volume set LNCS 10350 and 10351 constitutes the thoroughly refereed proceedings of the 30th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, held in Arras, France, in June 2017. The 70 revised full papers presented together with 45 short papers and 3 invited talks were carefully reviewed and selected from 180 submissions. They are organized in topical sections: constraints, planning, and optimization; data mining and machine learning; sensors, signal processing, and data fusion; recommender systems; decision support systems; knowledge representation and reasoning; navigation, control, and autonome agents; sentiment analysis and social media; games, computer vision; and animation; uncertainty management; graphical models: from theory to applications; anomaly detection; agronomy and artificial intelligence; applications of argumentation; intelligent systems in healthcare and mhealth for health outcomes; and innovative applications of textual analysis based on AI.
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• Constraints, planning, and optimization.- Data mining and machine learning.- Sensors, signal processing, and data fusion.- Recommender systems.- Decision support systems.- Knowledge representation and reasoning.- Navigation, control, and autonome agents.- Sentiment analysis and social media.- Games, computer vision, and animation.- Uncertainty management.- Graphical models: from theory to applications.- Anomaly detection.- Agronomy and artificial intelligence.- Applications of argumentation.- Intelligent systems in healthcare and mhealth for health outcomes.- Innovative applications of textual analysis based on AI.
• (source: Nielsen Book Data)

The two-volume set LNCS 10350 and 10351 constitutes the thoroughly refereed proceedings of the 30th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, held in Arras, France, in June 2017. The 70 revised full papers presented together with 45 short papers and 3 invited talks were carefully reviewed and selected from 180 submissions. They are organized in topical sections: constraints, planning, and optimization; data mining and machine learning; sensors, signal processing, and data fusion; recommender systems; decision support systems; knowledge representation and reasoning; navigation, control, and autonome agents; sentiment analysis and social media; games, computer vision; and animation; uncertainty management; graphical models: from theory to applications; anomaly detection; agronomy and artificial intelligence; applications of argumentation; intelligent systems in healthcare and mhealth for health outcomes; and innovative applications of textual analysis based on AI.
(source: Nielsen Book Data)

• Advances in Business ICT: New Ideas from Ongoing Research.- Verification of Temporal Knowledge Bases as an Important Aspect of Knowledge Management Processes in Organization.- The role of simulation performance in software-in-the-loop simulations.- Cognitum Ontorion: Knowledge Representation and Reasoning System.- Overview of Selected Business Process Semantization Techniques.- Selected Approaches Towards Taxonomy of Business Process Anomalies.- Hybrid framework for investment project portfolio selection.- Towards Predicting Stock Price Moves with Aid of Sentiment Analysis of Twitter Social Network Data and Big Data Processing Environment.- On a Property of Phase Correlation and Possibilities to Reduce the Walsh Function System.
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This book discusses the effective use of modern ICT solutions for business needs, including the efficient use of IT resources, decision support systems, business intelligence, data mining and advanced data processing algorithms, as well as the processing of large datasets (inter alia social networking such as Twitter and Facebook, etc.). The ability to generate, record and process qualitative and quantitative data, including in the area of big data, the Internet of Things (IoT) and cloud computing offers a real prospect of significant improvements for business, as well as the operation of a company within Industry 4.0. The book presents new ideas, approaches, solutions and algorithms in the area of knowledge representation, management and processing, quantitative and qualitative data processing (including sentiment analysis), problems of simulation performance, and the use of advanced signal processing to increase the speed of computation. The solutions presented are also aimed at the effective use of business process modeling and notation (BPMN), business process semantization and investment project portfolio selection. It is a valuable resource for researchers, data analysts, entrepreneurs and IT professionals alike, and the research findings presented make it possible to reduce costs, increase the accuracy of investment, optimize resources and streamline operations and marketing.
(source: Nielsen Book Data)

• Bio-inspired Computing.- E-Health and Computational Biology.- Human Computer Interaction.- Image and Signal Processing.- Mathematics for Neural Networks.- Self-organizing Networks.- Spiking Neurons.- Artificial Neural Networks in Industry ANNI'17.- Computational Intelligence Tools and Techniques for Biomedical Applications.- Assistive Rehabilitation Technology.- Computational Intelligence Methods for Time Series.- Machine Learning Applied to Vision and Robotics.- Human Activity Recognition for Health and Well-Being Applications.- Software Testing and Intelligent Systems.- Real World Applications of BCI Systems.- Machine Learning in Imbalanced Domains.- Surveillance and Rescue Systems and Algorithms for Unmanned Aerial Vehicles.- End-User Development for Social Robotics.- Artificial Intelligence and Games.- Supervised, Non-Supervised, Reinforcement and Statistical Algorithms. .
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This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, held in Cadiz, Spain, in June 2017. The 126 revised full papers presented in this double volume were carefully reviewed and selected from 199 submissions. The papers are organized in topical sections on Bio-inspired Computing; E-Health and Computational Biology; Human Computer Interaction; Image and Signal Processing; Mathematics for Neural Networks; Self-organizing Networks; Spiking Neurons; Artificial Neural Networks in Industry ANNI'17; Computational Intelligence Tools and Techniques for Biomedical Applications; Assistive Rehabilitation Technology; Computational Intelligence Methods for Time Series; Machine Learning Applied to Vision and Robotics; Human Activity Recognition for Health and Well-Being Applications; Software Testing and Intelligent Systems; Real World Applications of BCI Systems; Machine Learning in Imbalanced Domains; Surveillance and Rescue Systems and Algorithms for Unmanned Aerial Vehicles; End-User Development for Social Robotics; Artificial Intelligence and Games; and Supervised, Non-Supervised, Reinforcement and Statistical Algorithms.
(source: Nielsen Book Data)

• Bio-inspired Computing.- E-Health and Computational Biology.- Human Computer Interaction.- Image and Signal Processing.- Mathematics for Neural Networks.- Self-organizing Networks.- Spiking Neurons.- Artificial Neural Networks in Industry ANNI'17.- Computational Intelligence Tools and Techniques for Biomedical Applications.- Assistive Rehabilitation Technology.- Computational Intelligence Methods for Time Series.- Machine Learning Applied to Vision and Robotics.- Human Activity Recognition for Health and Well-Being Applications.- Software Testing and Intelligent Systems.- Real World Applications of BCI Systems.- Machine Learning in Imbalanced Domains.- Surveillance and Rescue Systems and Algorithms for Unmanned Aerial Vehicles.- End-User Development for Social Robotics.- Artificial Intelligence and Games.- Supervised, Non-Supervised, Reinforcement and Statistical Algorithms. .
• (source: Nielsen Book Data)

This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 14th International Work-Conference on Artificial Neural Networks, IWANN 2017, held in Cadiz, Spain, in June 2017. The 126 revised full papers presented in this double volume were carefully reviewed and selected from 199 submissions. The papers are organized in topical sections on Bio-inspired Computing; E-Health and Computational Biology; Human Computer Interaction; Image and Signal Processing; Mathematics for Neural Networks; Self-organizing Networks; Spiking Neurons; Artificial Neural Networks in Industry ANNI'17; Computational Intelligence Tools and Techniques for Biomedical Applications; Assistive Rehabilitation Technology; Computational Intelligence Methods for Time Series; Machine Learning Applied to Vision and Robotics; Human Activity Recognition for Health and Well-Being Applications; Software Testing and Intelligent Systems; Real World Applications of BCI Systems; Machine Learning in Imbalanced Domains; Surveillance and Rescue Systems and Algorithms for Unmanned Aerial Vehicles; End-User Development for Social Robotics; Artificial Intelligence and Games; and Supervised, Non-Supervised, Reinforcement and Statistical Algorithms.
(source: Nielsen Book Data)

• Natural Language Processing
• The relevance of the Named Entities in Authorship Attribution.- A compact representation for cross-domain short text clustering.- Characteristics of Most Frequent Spanish Verb-Noun Combinations.- Sentence Paraphrase Graphs: Classification Based on Predictive Models or Annotators Decisions.- Mathematical model of an ontological-semantic analyzer using basic ontological-semantic patterns.- CookingQA: A Question Answering System based on Cooking Ontology.- LEXIK. An Integrated System for Specialized Terminology.- Linguistic Restrictions in Automatic Translation from Written Spanish to MSL.- Intra-Document and Inter-Document Redundancy on Multi-Document Summarization.- Framework for searching judicial precedents based on Automatic summarization.- Discriminatory capacity of the most representative phonemes in Spanish: an evaluation for forensic speech recognition.- A Speech-Based Web Co-Authoring Platform for the Blind.- Social Networks and Opinion Mining.- Friends and Enemies of Clinton and Trump: Using Context for Detecting Stance in Political Tweets.- Additive Regularization for Topic Modeling in Sociological Studies of User-Generated Texts.- Effect of the inclusion of non-newsworthy messages in credibility assessment.- On the impact of neighborhood selection strategies for recommender systems in LBSNs.- Fuzzy Logic.- For Multi-Interval-Valued Fuzzy Sets, Centroid Defuzzification Is Equivalent to Defuzzifying Its Interval Hull: A Theorem.- Metric Spaces Under Interval Uncertainty: Towards an Adequate Definition.- A study of parameter dynamic adaptation with fuzzy logic for the grey wolf optimizer algorithm.- Interval Type-2 fuzzy logic for parameter adaptation in the gravitational search algorithm.- Water cycle algorithm with fuzzy logic for dynamic adaptation of parameters.- Off-line tuning of a PID controller using Type-2 Fuzzy Logic.- Detection of faults in induction motors using texture-based features and fuzzy inference.- Time Series Analysis and Forecasting.- Trend Detection in Gold Worth using Regression.- Queries to Internet as a Tool for Analysis of Regional Police Work and Forecast of Crimes in Regions.- Creating Collections of Descriptors of Events and Processes Based on Internet Queries.- Planning and Scheduling.- Using a Grammar Checker to Validate Compliance of Processes with Workflow Models.- On Verification of Workflow and Planning Domain Models using Attribute Grammars.- Tramp Ship Scheduling Problem with Berth Allocation Considerations and Time-dependent Constraints.- Hierarchical Task Model for Resource Failure Recovery in Production Scheduling.- A multi-objective hospital operating room planning and scheduling problem using compromise programming.- Solving Manufacturing Cell Design Problems using the Black Hole Algorithm.- Image Processing and Computer Vision.- Efficient Computation of the Euler Number of a 2-D Binary of Image.- Image filter based on block matching and principal component analysis.- Support to the diagnosis of the Pap test, using computer algorithms of digital image processing.- Implementation of Computer Vision Guided Peg-Hole Insertion Task Performed by Robot through LabVIEW.- Object Tracking Based on Modified TLD Framework Using Compressive Sensing Features.- Parameter characterization of complex wavelets and its use in 3D reconstruction.- Customer Analysis via Video Analytics: Customer Detection with Multiple Cues.- Methodology for Automatic Collection of Vehicle Traffic Data by Object Tracking.- Robotics.- GPS-based curve estimation for an adaptive pure pursuit algorithm.- Collective motion of a swarm of simulated quadrotors using repulsion, attraction and orientation rules.- Design and simulation of a new lower exoskeleton for rehabilitation of patients with paraplegia.- Sensorial system for obtaining the angles of the human movement in the coronal and sagittal anatomical planes.
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The two-volume set LNAI 10061 and 10062 constitutes the proceedings of the 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, held in Cancun, Mexico, in October 2016. The total of 86 papers presented in these two volumes was carefully reviewed and selected from 238 submissions. The contributions were organized in the following topical sections: Part I: natural language processing; social networks and opinion mining; fuzzy logic; time series analysis and forecasting; planning and scheduling; image processing and computer vision; robotics. Part II: general; reasoning and multi-agent systems; neural networks and deep learning; evolutionary algorithms; machine learning; classification and clustering; optimization; data mining; graph-based algorithms; and intelligent learning environments.
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• Requirements analysis.-Business analysis:- Ambient Assisted Living:- Computing for Healthcare:- Data Science:-Data Analysis.- Business Intelligence.- Ontology.- Software Quality.- Model Quality.
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This book constitutes the refereed proceedings of five workshops and a symposium, held at the 36th International Conference on Conceptual Modeling, ER 2017, in Valencia, Spain in November 2017. The 21 revised full papers were carefully reviewed and selected out of 47 submissions to the following events: AHA 2017 - 3rd International Workshop on Modeling for Ambient Assistance and Healthy Ageing MoBiD 2017 - 6th International Workshop on Modeling and Management of Big Data MREBA 2017 - 4th International Workshop on Conceptual Modeling in Requirements and Business Analysis OntoCom 2017 - 5th International Workshop on Ontologies and Conceptual Modeling QMMQ 2017 - 4th Workshop on Quality of Models and Models of Quality.
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• PART 1, Data mining, machine learning, knowledge discovery, Tensor Networks for Dimensionality Reduction, Big Data and Deep Learning.- Local Data Characteristics in Learning Classifiers from Imbalanced Data.- Similarity dimensions of semantic ontologies.- Some interesting phenomenon occurring during self-learning process with its psychological interpretation.- PART 2, Neural networks and connectionist systems, On the interpretation and characterization of echo state networks dynamics: A complex systems perspective.- Optimization of Ensemble Neural Networks with Type-1 and Interval Type-2 Fuzzy Integration for Forecasting the Taiwan Stock Exchange.- Deep Neural Networks - A Brief History.- PART 3, Intelligent technologies in systems modeling, Techniques for Construction and Integration of Rule Bases.- New Aspects of Interpretability of Fuzzy Systems for Nonlinear Modeling.- On the intuitionistic fuzzy sets of n-th type.-
• PART 4. Intelligent technologies in decision making, optimization and control, MCTS/UCT in solving real-life problems.- Interactive cone contraction for evolutionary mutliple objective optimization.- A review of fuzzy and mathematic methods for dynamic parameter adaptation in the firefly algorithm.-
• PART 5. Applications of intelligent technologies Computational Intelligence Methods in Personalized Pharmacotherapy.- Embodying Intelligence in Autonomous and Robotic Systems with the Use of Cognitive Psychology and Motivation Theories.- Evolutionary Approach for Automatic Design of PID Controllers.- Fuzzy-genetic approach to identity verification using a handwritten signature.- A method of design and optimization for SiC-based grid-connected AC-DC converters.
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This book is a tribute to Professor Jacek Zurada, who is best known for his contributions to computational intelligence and knowledge-based neurocomputing. It is dedicated to Professor Jacek Zurada, Full Professor at the Computational Intelligence Laboratory, Department of Electrical and Computer Engineering, J.B. Speed School of Engineering, University of Louisville, Kentucky, USA, as a token of appreciation for his scientific and scholarly achievements, and for his longstanding service to many communities, notably the computational intelligence community, in particular neural networks, machine learning, data analyses and data mining, but also the fuzzy logic and evolutionary computation communities, to name but a few. At the same time, the book recognizes and honors Professor Zurada's dedication and service to many scientific, scholarly and professional societies, especially the IEEE (Institute of Electrical and Electronics Engineers), the world's largest professional technical professional organization dedicated to advancing science and technology in a broad spectrum of areas and fields. The volume is divided into five major parts, the first of which addresses theoretic, algorithmic and implementation problems related to the intelligent use of data in the sense of how to derive practically useful information and knowledge from data. In turn, Part 2 is devoted to various aspects of neural networks and connectionist systems. Part 3 deals with essential tools and techniques for intelligent technologies in systems modeling and Part 4 focuses on intelligent technologies in decision-making, optimization and control, while Part 5 explores the applications of intelligent technologies.
(source: Nielsen Book Data)

• Improving Chairlift Security with Deep Learning.- Discovering motifs with variants in music databases.- Biclustering Multivariate Time Series.- Visualization of Topic-Sentiment Dynamics in Crowdfunding Projects.- Regression tree for bandits models in A/B testing.- Seasonal Variation in Collective Mood via Twitter Content and Medical Purchases.- Skin Cancer Detection in Dermoscopy Images Using Sub-Region Features.- Bucket Selection: A Model-Independent Diverse Selection Strategy for Widening.- Interactive Pattern Sampling for Characterizing Unlabeled Data.- Searching for Spatio-Temporal-Keyword Patterns in Semantic Trajectories.- Natural Language Analysis of Online Health Forums.- Freudian Slips: Analysing the Internal Representations of a Neural Network from its Mistakes.- KAPMiner: Mining ordered association rules with constraints.- A Dynamic Adaptive Questionnaire for Improved Disease Diagnostics.- ABIDE: Querying Time-Evolving Sequences of Temporal Intervals.- The Actors of History: Narrative Network Analysis Reveals the Institutions of Power in British Society Between 1800-1950.- Learning DTW-Preserving Shapelets.- Droplet Ensemble Learning on Drifting Data Streams.- Predictive clustering trees for hierarchical multi-target regression.- Identifying novel features from specimen data for the prediction of valuable field trips.- Adapting supervised classifiation algorithms to arbitrary weak label scenarios.- The Combination of Decision in Crowds When The Number of Reliable Annotator is Rare.- Estimating Sequence Similarity from Contig Sets.- Computational Topology Techniques for Characterizing Time-Series Data.- Improving Cold-Start Recommendations with Social-Media Trends and Reputations.- Hierarchical Novelty Detection.- Towards automatic evaluation of asphalt irregularity using smartphone's Sensors.- A structural benchmark for logical argumentation frameworks.
• (source: Nielsen Book Data)

This book constitutes the conference proceedings of the 16th International Symposium on Intelligent Data Analysis, which was held in October 2017 in London, UK. The 28 full papers presented in this book were carefully reviewed and selected from 66 submissions. The traditional focus of the IDA symposium series is on end-to-end intelligent support for data analysis. IDA solicits papers on all aspects of intelligent data analysis, including papers on intelligent support for modelling and analyzing data from complex, dynamical systems.
(source: Nielsen Book Data)

• Classification and deep learning.- Social network and graph mining.- Privacy-preserving mining and security/risk applications.- Spatio-temporal and sequential data mining.- Clustering and anomaly detection.- Recommender system.- Feature selection.- Text and opinion mining.- Clustering and matrix factorization.- Dynamic, stream data mining.- Novel models and algorithms.- Behavioral data mining.- Graph clustering and community detection.- Dimensionality reduction.
• (source: Nielsen Book Data)

This two-volume set, LNAI 10234 and 10235, constitutes the thoroughly refereed proceedings of the 21st Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2017, held in Jeju, South Korea, in May 2017. The 129 full papers were carefully reviewed and selected from 458 submissions. They are organized in topical sections named: classification and deep learning; social network and graph mining; privacy-preserving mining and security/risk applications; spatio-temporal and sequential data mining; clustering and anomaly detection; recommender system; feature selection; text and opinion mining; clustering and matrix factorization; dynamic, stream data mining; novel models and algorithms; behavioral data mining; graph clustering and community detection; dimensionality reduction.
(source: Nielsen Book Data)

• Part I: Online learning of a weighted selective naive Bayes classifier with non-convex optimization
• On making skyline queries resistant to outliers
• Adaptive Down-Sampling and Dimension Reduction in Time Elastic Kernel Machines for Efficient Recognition of Isolated Gestures
• Exact and Approximate Minimal Pattern Mining
• Part II: Comparison of proximity measures for a topological discrimination
• Comparison of linear modularization criteria using the relational formalism, an approach to easily identify resolution limit
• A novel approach to feature selection based on quality estimation metrics
• Ultrametricity of Dissimilarity Spaces and Its Significance for Data Mining
• Part III: SMERA: Semantic Mixed Approach for Web Query Expansion and Reformulation
• Multi-layer ontologies for integrated 3D shape segmentation and annotation
• Ontology Alignment Using Web Linked Ontologies as Background Knowledge
• LIAISON: reconciLIAtion of Individuals profiles across SOcial Networks
• Clustering of Links and Clustering of Nodes: Fusion of Knowledge in Social Networks.

This book presents a collection of representative and novel work in the field of data mining, knowledge discovery, clustering and classification, based on expanded and reworked versions of a selection of the best papers originally presented in French at the EGC 2014 and EGC 2015 conferences held in Rennes (France) in January 2014 and Luxembourg in January 2015. The book is in three parts: The first four chapters discuss optimization considerations in data mining. The second part explores specific quality measures, dissimilarities and ultrametrics. The final chapters focus on semantics, ontologies and social networks. Written for PhD and MSc students, as well as researchers working in the field, it addresses both theoretical and practical aspects of knowledge discovery and management.

• A Combined Approach for Ontology Enrichment from Textual and Open Data.- C-SPARQL Extension for Sampling RDF Graphs Streams.- Efficiency Analysis of ASP Encodings for Sequential Pattern Mining Tasks.
• (source: Nielsen Book Data)

This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of "Knowledge Discovery and Management" (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories. The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC'2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.
(source: Nielsen Book Data)