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This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web. Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed: •    Sentic Computing's multi-disciplinary approach to sentiment  analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference •    Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text •    Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain  and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems.

Neurology --- Medicine --- Health & Biological Sciences --- Semantic computing. --- Data mining. --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Medicine. --- Neurosciences. --- Semantics. --- Cognitive psychology. --- Biomedicine. --- Data Mining and Knowledge Discovery. --- Cognitive Psychology. --- Database searching --- Computer science --- Electronic data processing --- Semantics --- Consciousness. --- Apperception --- Mind and body --- Perception --- Philosophy --- Psychology --- Spirit --- Self --- Formal semantics --- Semasiology --- Semiology (Semantics) --- Comparative linguistics --- Information theory --- Language and languages --- Lexicology --- Meaning (Psychology) --- Neural sciences --- Neurological sciences --- Neuroscience --- Medical sciences --- Nervous system --- Psychology, Cognitive --- Cognitive science

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Natural language processing (Computer science) --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- Tractament del llenguatge natural (Informàtica)

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This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web. Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain. Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed: • Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference • Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text • Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems.

Cognitive psychology --- Neuropathology --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Lexicology. Semantics --- neurologie --- datamining --- semantiek --- cognitieve psychologie --- data acquisition

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The abundance of text available in social media and health-related forums and blogs have recently attracted the interest of the public health community to use these sources for opinion mining. This book presents a lexicon-based approach to sentiment analysis in the bio-medical domain, i.e., WordNet for Medical Events (WME). This book gives an insight in handling unstructured textual data and converting it to structured machine-processable data in the bio-medical domain. The readers will discover the following key novelties: 1) development of a bio-medical lexicon: WME expansion and WME enrichment with additional features.; 2) ensemble of machine learning and computational creativity; 3) development of microtext analysis techniques to overcome the inconsistency in social communication. It will be of interest to researchers in the fields of socially-intelligent human-machine interaction and biomedical text mining.

Medicine. --- Computer science. --- Computational intelligence. --- Biomedicine. --- Biomedicine general. --- Computational Intelligence. --- Computer Science, general. --- Intelligence, Computational --- Informatics --- Clinical sciences --- Medical profession --- Data mining. --- Electronic data processing. --- Medical sciences --- Basic medical sciences --- Basic sciences, Medical --- Biomedical sciences --- Health sciences --- Preclinical sciences --- Sciences, Medical --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Computer programs. --- Artificial intelligence --- Soft computing --- Science --- Human biology --- Life sciences --- Pathology --- Physicians --- Medicine --- Computers --- Office practice --- Database searching --- Automation --- Engineering. --- Construction --- Industrial arts --- Technology --- Health Workforce --- Biomedicine, general.

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This book presents a systematic application of recent advances in artificial intelligence (AI) to the problem of asset management. While natural language processing and text mining techniques, such as semantic representation, sentiment analysis, entity extraction, commonsense reasoning, and fact checking have been evolving for decades, finance theories have not yet fully considered and adapted to these ideas. In this unique, readable volume, the authors discuss integrating textual knowledge and market sentiment step-by-step, offering readers new insights into the most popular portfolio optimization theories: the Markowitz model and the Black-Litterman model. The authors also provide valuable visions of how AI technology-based infrastructures could cut the cost of and automate wealth management procedures. This inspiring book is a must-read for researchers and bankers interested in cutting-edge AI applications in finance.

Medicine. --- Data mining. --- Artificial intelligence. --- E-business. --- Electronic commerce. --- E-commerce. --- Biomedicine, general. --- Data Mining and Knowledge Discovery. --- Artificial Intelligence. --- e-Business/e-Commerce. --- e-Commerce/e-business. --- Cybercommerce --- E-business --- E-commerce --- E-tailing --- eBusiness --- eCommerce --- Electronic business --- Internet commerce --- Internet retailing --- Online commerce --- Web retailing --- Commerce --- Information superhighway --- 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 --- Algorithmic knowledge discovery --- Factual data analysis --- KDD (Information retrieval) --- Knowledge discovery in data --- Knowledge discovery in databases --- Mining, Data --- Database searching --- Health Workforce --- Asset allocation. --- Allocation of assets --- Investments --- Portfolio management --- Intel·ligència artificial --- Ciència cognitiva --- Mètodes de simulació --- Processament de dades --- Sistemes autoorganitzatius --- Aprenentatge automàtic --- Demostració automàtica de teoremes --- Intel·ligència artificial distribuïda --- Intel·ligència computacional --- Sistemes adaptatius --- Tractament del llenguatge natural (Informàtica) --- Raonament qualitatiu --- Representació del coneixement (Teoria de la informació) --- Sistemes de pregunta i resposta --- Traducció automàtica --- Visió per ordinador --- Xarxes neuronals (Informàtica) --- Xarxes semàntiques (Teoria de la informació) --- Agents intel·ligents (Programes d'ordinador) --- Programació per restriccions --- Vida artificial --- Intel·ligència artificial.