Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This book is the result of a group of researchers from different disciplines asking themselves one question: what does it take to develop a computer interface that listens, talks, and can answer questions in a domain? First, obviously, it takes specialized modules for speech recognition and synthesis, human interaction management (dialogue, input fusion, andmultimodal output fusion), basic question understanding, and answer finding. While all modules are researched as independent subfields, this book describes the development of state-of-the-art modules and their integration into a single, working application capable of answering medical (encyclopedic) questions such as "How long is a person with measles contagious?" or "How can I prevent RSI?". The contributions in this book, which grew out of the IMIX project funded by the Netherlands Organisation for Scientific Research, document the development of this system, but also address more general issues in natural language processing, such as the development of multidimensional dialogue systems, the acquisition of taxonomic knowledge from text, answer fusion, sequence processing for domain-specific entity recognition, and syntactic parsing for question answering. Together, they offer an overview of the most important findings and lessons learned in the scope of the IMIX project, making the book of interest to both academic and commercial developers of human-machine interaction systems in Dutch or any other language. Highlights include: integrating multi-modal input fusion in dialogue management (Van Schooten and Op den Akker), state-of-the-art approaches to the extraction of term variants (Van der Plas, Tiedemann, and Fahmi; Tjong Kim Sang, Hofmann, and De Rijke), and multi-modal answer fusion (two chapters by Van Hooijdonk, Bosma, Krahmer, Maes, Theune, and Marsi). Watch the IMIX movie at www.nwo.nl/imix-film . Like IBM's Watson, the IMIX system described in the book gives naturally phrased responses to naturally posed questions. Where Watson can only generate synthetic speech, the IMIX system also recognizes speech. On the other hand, Watson is able to win a television quiz, while the IMIX system is domain-specific, answering only to medical questions. "The Netherlands has always been one of the leaders in the general field of Human Language Technology, and IMIX is no exception. It was a very ambitious program, with a remarkably successful performance leading to interesting results. The teams covered a remarkable amount of territory in the general sphere of multimodal  question answering and information delivery, question answering, information extraction and component technologies." Eduard Hovy, USC, USA, Jon Oberlander, University of Edinburgh, Scotland, and Norbert Reithinger, DFKI, Germany .

Human-computer interaction. --- System design. --- User interfaces (Computer systems) -- Design. --- Multimodal user interfaces (Computer systems) --- Multimedia systems --- Information storage and retrieval systems --- Question-answering systems --- Engineering & Applied Sciences --- Computer Science --- Question-answering systems. --- Computer science. --- Information storage and retrieval. --- Multimedia information systems. --- User interfaces (Computer systems). --- Computer Science. --- Multimedia Information Systems. --- Signal, Image and Speech Processing. --- User Interfaces and Human Computer Interaction. --- Information Storage and Retrieval. --- Interfaces, User (Computer systems) --- Human-machine systems --- Human-computer interaction --- Computer-based multimedia information systems --- Multimedia computing --- Multimedia information systems --- Multimedia knowledge systems --- Informatics --- Science --- Artificial intelligence --- Problem solving --- Multimedia systems. --- Information storage and retrieva. --- 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 --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Optical data processing --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication)

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Memory-based language processing - a machine learning and problem solving method for language technology - is based on the idea that the direct reuse of examples using analogical reasoning is more suited for solving language processing problems than the application of rules extracted from those examples. This book discusses the theory and practice of memory-based language processing, showing its comparative strengths over alternative methods of language modelling. Language is complex, with few generalizations, many sub-regularities and exceptions, and the advantage of memory-based language processing is that it does not abstract away from this valuable low-frequency information. By applying the model to a range of benchmark problems, the authors show that for linguistic areas ranging from phonology to semantics, it produces excellent results. They also describe TiMBL, a software package for memory-based language processing. The first comprehensive overview of the approach, this book will be invaluable for computational linguists, psycholinguists and language engineers.

Artificial intelligence. Robotics. Simulation. Graphics --- Mathematical linguistics --- Computational linguistics --- Learning, Psychology of --- Natural language processing (Computer science) --- 800:311 --- 800:311 Kwantitatieve linguistiek. Computerlinguistiek --- Kwantitatieve linguistiek. Computerlinguistiek --- NLP (Computer science) --- Artificial intelligence --- Electronic data processing --- Human-computer interaction --- Semantic computing --- Learning --- Psychology of learning --- Educational psychology --- Comprehension --- Learning ability --- Automatic language processing --- Language and languages --- Language data processing --- Linguistics --- Natural language processing (Linguistics) --- Applied linguistics --- Cross-language information retrieval --- Multilingual computing --- Psychological aspects --- Data processing --- Human-computer interaction. --- Computer-human interaction --- Human factors in computing systems --- Interaction, Human-computer --- Human engineering --- User-centered system design --- User interfaces (Computer systems) --- Computational linguistics. --- Learning, Psychology of. --- Computerlinguïstiek. --- Linguïstiek en gegevensverwerking. --- Natural language processing. --- Natuurlijke taalverwerking. --- Taaltechnologie. --- Arts and Humanities --- Language & Linguistics

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The digital age has had a profound effect on our cultural heritage and the academic research that studies it. Staggering amounts of objects, many of them of a textual nature, are being digitised to make them more readily accessible to both experts and laypersons. Besides a vast potential for more effective and efficient preservation, management, and presentation, digitisation offers opportunities to work with cultural heritage data in ways that were never feasible or even imagined.  To explore and exploit these possibilities, an interdisciplinary approach is needed, bringing together experts from cultural heritage, the social sciences and humanities on the one hand, and information technology on the other. Due to a prevalence of textual data in these domains, language technology has a crucial role to play in this endeavour. Language technology can break through the "Google barrier" by offering the potential to analyse texts at advanced levels, extracting information and knowledge at the level of the humanities or social sciences researcher, who wants to know about the who, what, where, and when, but also the how and the why. At the same time cultural heritage data poses considerable challenges for existing language technology: technology aimed at "generic" language has to face such disparate problems as historical language variation, OCR digitisation errors, and near-extinct academic expertise.   This book is primarily intended for researchers in information technology and language processing who would like to receive a state-of-the-art overview of the whole breadth of the new and vibrant field of language technology for cultural heritage and its associated academic research in the humanities and social sciences. Researchers working in the target domains of cultural heritage, the social sciences and humanities will also find this book useful, as it provides an overview of how language technology can help them with their information needs. The book covers applications ranging from pre-processing and data cleaning, to the adaptation and compilation of linguistic resources, to personalisation, narrative analysis, visualisation and retrieval.  .

Browsers (Computer programs). --- Computational linguistics. --- Electronic information resource searching. --- Humanities -- Digital libraries. --- Linguistic analysis (Linguistics). --- User interfaces (Computer systems) -- Design. --- Natural language processing (Computer science) --- Computational linguistics --- Engineering & Applied Sciences --- Mechanical Engineering --- Computer Science --- Mechanical Engineering - General --- Information Technology --- Artificial Intelligence --- NLP (Computer science) --- Automatic language processing --- Language and languages --- Language data processing --- Linguistics --- Natural language processing (Linguistics) --- Data processing --- Computer science. --- Information storage and retrieval. --- Artificial intelligence. --- Pattern recognition. --- Computer Science. --- Artificial Intelligence (incl. Robotics). --- Pattern Recognition. --- Language Translation and Linguistics. --- Information Storage and Retrieval. --- Applied linguistics --- Cross-language information retrieval --- Mathematical linguistics --- Multilingual computing --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- 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 --- Informatics --- Science --- Artificial intelligence --- Human-computer interaction --- Semantic computing --- Optical pattern recognition. --- Natural language processing (Computer science). --- Information storage and retrieva. --- Artificial Intelligence. --- Natural Language Processing (NLP). --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- 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

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The morphology of Arabic poses special challenges to computational natural language processing systems. The exceptional degree of ambiguity in the writing system, the rich morphology, and the highly complex word formation process of roots and patterns all contribute to making computational approaches to Arabic very challenging. Indeed many computational linguists across the world have taken up this challenge over time, and many of the researchers with a track record in this research area have contributed to this book. The book's subtitle aims to reflect that widely different computational approaches to the Arabic morphological system have been proposed. These accounts fall into two main paradigms: the knowledge-based and the empirical. Since morphological knowledge plays an essential role in any higher-level understanding and processing of Arabic text, the book also features a part on the role of Arabic morphology in larger applications, i.e. Information Retrieval (IR) and Machine Translation (MT).

Computer architecture. Operating systems --- Information systems --- Computer. Automation --- Translation science --- Mathematical linguistics --- Linguistics --- Arabic languages --- Semitic languages --- IR (information retrieval) --- spraaktechnologie --- vertalen --- linguïstiek --- taalstudie