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Information extraction regards the processes of structuring and combining content that is explicitly stated or implied in one or multiple unstructured information sources. It involves a semantic classification and linking of certain pieces of information and is considered as a light form of content understanding by the machine. Currently, there is a considerable interest in integrating the results of information extraction in retrieval systems, because of the growing demand for search engines that return precise answers to flexible information queries. Advanced retrieval models satisfy that need and they rely on tools that automatically build a probabilistic model of the content of a (multi-media) document. The book focuses on content recognition in text. It elaborates on the past and current most successful algorithms and their application in a variety of domains (e.g., news filtering, mining of biomedical text, intelligence gathering, competitive intelligence, legal information searching, and processing of informal text). An important part discusses current statistical and machine learning algorithms for information detection and classification and integrates their results in probabilistic retrieval models. The book also reveals a number of ideas towards an advanced understanding and synthesis of textual content. The book is aimed at researchers and software developers interested in information extraction and retrieval, but the many illustrations and real world examples make it also suitable as a handbook for students.

Information storage and retrieval systems --- Academic collection --- 681.3*H3 --- 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 --- Information storage and retrieval --- Information storage and retrieval systems. --- Information organzation. --- Information organization. --- Organization of information --- Information science --- Library science. --- Information storage and retrieval. --- Artificial intelligence. --- Natural language processing (Computer science). --- Optical pattern recognition. --- Computer industry. --- Library Science. --- Information Storage and Retrieval. --- Artificial Intelligence. --- Natural Language Processing (NLP). --- Pattern Recognition. --- The Computer Industry. --- Electronic industries --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- 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 --- Librarianship --- Library economy --- Bibliography --- Documentation --- Pattern recognition. --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Data centers