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This volume gives an overview of research done by CCI faculty in the area of Information & Intelligent Systems. Presented papers focus on recent advances in four major directions: Complex Systems, Knowledge Management, Knowledge Discovery, and Visualization. A major reason for producing this book was to demonstrate a new, important thrust in academic research where college-wide interdisciplinary efforts are brought to bear on large, general, and important problems. As shown in the research described here, these efforts need not be formally organized joint undertakings (through parts could be) but are rather a convergence of interests around grand themes. Taken together, the sections and chapters in this book reveal a variety of methods and tools that can be applied to quite diverse types of data and analysis problems but where each produces knowledge and features that can be combined, organized, explored, understood, and used in common ways (for example, through interactive visualization interfaces).

Computational intelligence --- Information technology --- Computer simulation --- Applied Mathematics --- Civil Engineering --- Computer Science --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Artificial intelligence. --- Information technology. --- Knowledge management. --- Management of knowledge assets --- IT (Information technology) --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Computer science. --- Data mining. --- Image processing. --- Applied mathematics. --- Engineering mathematics. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Data Mining and Knowledge Discovery. --- Image Processing and Computer Vision. --- Appl.Mathematics/Computational Methods of Engineering. --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Engineering --- Engineering analysis --- Mathematical analysis --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Informatics --- Science --- Mathematics --- Management --- Intellectual capital --- Organizational learning --- Technology --- Telematics --- Information superhighway --- Knowledge management --- Computer vision. --- Artificial Intelligence. --- Mathematical and Computational Engineering. --- Machine vision --- Vision, Computer --- Artificial intelligence --- Image processing --- Pattern recognition systems --- Optical data processing. --- Optical computing --- Visual data processing --- Integrated optics --- Photonics --- Computers --- Optical equipment

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Sound waves propagate through various media, and allow communication or entertainment for us, humans. Music we hear or create can be perceived in such aspects as rhythm, melody, harmony, timbre, or mood. All these elements of music can be of interest for users of music information retrieval systems. Since vast music repositories are available for everyone in everyday use (both in private collections, and in the Internet), it is desirable and becomes necessary to browse music collections by contents. Therefore, music information retrieval can be potentially of interest for every user of computers and the Internet. There is a lot of research performed in music information retrieval domain, and the outcomes, as well as trends in this research, are certainly worth popularizing. This idea motivated us to prepare the book on Advances in Music Information Retrieval. It is divided into four sections: MIR Methods and Platforms, Harmony, Music Similarity, and Content Based Identification and Retrieval. Glossary of basic terms is given at the end of the book, to familiarize readers with vocabulary referring to music information retrieval.

Information storage and retrieval systems --- Music --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Music, Dance, Drama & Film --- Music Literature --- Applied Mathematics --- Civil Engineering --- Data processing --- Musical analysis --- Data processing. --- Analysis, Musical --- Analytical guides (Music) --- Hermeneutics (Music) --- Music analysis --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Analysis, appreciation --- Analytical guides --- Engineering. --- Music. --- Artificial intelligence. --- Applied mathematics. --- Engineering mathematics. --- Appl.Mathematics/Computational Methods of Engineering. --- Artificial Intelligence (incl. Robotics). --- Signal, Image and Speech Processing. --- Engineering --- Engineering analysis --- Mathematical analysis --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Art music --- Art music, Western --- Classical music --- Musical compositions --- Musical works --- Serious music --- Western art music --- Western music (Western countries) --- Construction --- Industrial arts --- Technology --- Mathematics --- Music theory --- Music appreciation --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Instruction and study --- Mathematical and Computational Engineering. --- Artificial Intelligence. --- Signal processing. --- Image processing. --- Speech processing systems. --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication) --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers

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This book presents the Recommender System for Improving Customer Loyalty. New and innovative products have begun appearing from a wide variety of countries, which has increased the need to improve the customer experience. When a customer spends hundreds of thousands of dollars on a piece of equipment, keeping it running efficiently is critical to achieving the desired return on investment. Moreover, managers have discovered that delivering a better customer experience pays off in a number of ways. A study of publicly traded companies conducted by Watermark Consulting found that from 2007 to 2013, companies with a better customer service generated a total return to shareholders that was 26 points higher than the S&P 500. This is only one of many studies that illustrate the measurable value of providing a better service experience. The Recommender System presented here addresses several important issues. (1) It provides a decision framework to help managers determine which actions are likely to have the greatest impact on the Net Promoter Score. (2) The results are based on multiple clients. The data mining techniques employed in the Recommender System allow users to “learn” from the experiences of others, without sharing proprietary information. This dramatically enhances the power of the system. (3) It supplements traditional text mining options. Text mining can be used to identify the frequency with which topics are mentioned, and the sentiment associated with a given topic. The Recommender System allows users to view specific, anonymous comments associated with actual customers. Studying these comments can provide highly accurate insights into the steps that can be taken to improve the customer experience. (4) Lastly, the system provides a sensitivity analysis feature. In some cases, certain actions can be more easily implemented than others. The Recommender System allows managers to “weigh” these actions and determine which ones would have a greater impact.

Recommender systems (Information filtering) --- Customer loyalty. --- Frequent buyer programs --- Frequent shopper programs --- Consumer behavior --- Loyalty --- Consumer satisfaction --- Engines, Recommendation (Information filtering) --- Recommendation engines (Information filtering) --- Recommendation systems (Information filtering) --- Systems, Recommendation (Information filtering) --- Systems, Recommender (Information filtering) --- Information filtering systems --- Engineering. --- Customer relations-Management. --- Data mining. --- Optical pattern recognition. --- Computational Intelligence. --- Customer Relationship Management. --- Data Mining and Knowledge Discovery. --- Pattern Recognition. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Construction --- Industrial arts --- Technology --- Computational intelligence. --- Customer relations—Management. --- Pattern recognition. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Intelligence, Computational --- Artificial intelligence --- Soft computing

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This book constitutes the refereed proceedings of the 21st International Symposium on Methodologies for Intelligent Systems, ISMIS 2014, held in Roskilde, Denmark, in June 2014. The 61 revised full papers were carefully reviewed and selected from 111 submissions. The papers are organized in topical sections on complex networks and data stream mining; data mining methods; intelligent systems applications; knowledge representation in databases and systems; textual data analysis and mining; special session: challenges in text mining and semantic information retrieval; special session: warehousing and OLAPing complex, spatial and spatio-temporal data; ISMIS posters.

Intelligent agents (Computer software) --- Artificial intelligence --- Artificial intelligence. --- Data mining. --- Database management. --- Information storage and retrieva. --- Computer science. --- Artificial Intelligence. --- Data Mining and Knowledge Discovery. --- Database Management. --- Information Storage and Retrieval. --- Information Systems Applications (incl. Internet). --- User Interfaces and Human Computer Interaction. --- Information storage and retrieval. --- Information retrieval. --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Bionics --- Cognitive science --- Digital computer simulation --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Informatics --- Science --- Data retrieval --- Data storage --- Discovery, Information --- Information discovery --- Information storage and retrieval --- Retrieval of information --- Documentation --- Information science --- Information storage and retrieval systems --- Information storage and retrieval systems. --- Automatic data storage --- Automatic information retrieval --- Automation in documentation --- Computer-based information systems --- Data processing systems --- Data storage and retrieval systems --- Discovery systems, Information --- Information discovery systems --- Information processing systems --- Information retrieval systems --- Machine data storage and retrieval --- Mechanized information storage and retrieval systems --- Computer systems --- Electronic information resources --- Data libraries --- Digital libraries --- Information organization --- Information retrieval --- Application software. --- User interfaces (Computer systems). --- Interfaces, User (Computer systems) --- Human-machine systems --- Human-computer interaction --- Application computer programs --- Application computer software --- Applications software --- Apps (Computer software) --- Computer software

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The book presents a knowledge discovery based approach to build a recommender system supporting a physician in treating tinnitus patients with the highly successful method called Tinnitus Retraining Therapy. It describes experiments on extracting novel knowledge from the historical dataset of patients treated by Dr. P. Jastreboff so that to better understand factors behind therapy's effectiveness and better personalize treatments for different profiles of patients. The book is a response for a growing demand of an advanced data analytics in the healthcare industry in order to provide better care with the data driven decision-making solutions. The potential economic benefits of applying computerized clinical decision support systems include not only improved efficiency in health care delivery (by reducing costs, improving quality of care and patient safety), but also enhancement in treatment's standardization, objectivity and availability in places of scarce expert's knowledge on this difficult to treat hearing disorder. Furthermore, described approach could be used in assessment of the clinical effectiveness of evidence-based intervention of various proposed treatments for tinnitus.

Engineering. --- Health informatics. --- Artificial intelligence. --- Computational intelligence. --- Computational Intelligence. --- Artificial Intelligence (incl. Robotics). --- Health Informatics. --- Intelligence, Computational --- AI (Artificial intelligence) --- Artificial thinking --- Electronic brains --- Intellectronics --- Intelligence, Artificial --- Intelligent machines --- Machine intelligence --- Thinking, Artificial --- Clinical informatics --- Health informatics --- Medical information science --- Construction --- Artificial intelligence --- Bionics --- Cognitive science --- Digital computer simulation --- Electronic data processing --- Logic machines --- Machine theory --- Self-organizing systems --- Simulation methods --- Fifth generation computers --- Neural computers --- Information science --- Medicine --- Industrial arts --- Technology --- Data processing --- Soft computing --- Medical records --- Artificial Intelligence. --- Data processing. --- EHR systems --- EHR technology --- EHRs (Electronic health records) --- Electronic health records --- Electronic medical records --- EMR systems --- EMRs (Electronic medical records) --- Information storage and retrieval systems --- Medical care --- Tinnitus --- Treatment. --- Buzzing in the ears --- Ear buzzing --- Ear ringing --- Ringing in the ears --- Hearing disorders --- Medical informatics.