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TY  - BOOK
ID  - 14302767
TI  - Structure discovery in natural language
AU  - Biemann, Chris.
AU  - Bosch, Antal van den.
PY  - 2012
SN  - 3642259227 9786613452542 1283452545 3642259235 3642442307
PB  - Heidelberg : Springer,
DB  - UniCat
KW  - Information Technology
KW  - Artificial Intelligence
KW  - Data mining.
KW  - Information retrieval.
KW  - Natural language processing (Computer science).
KW  - Natural language processing (Computer science)
KW  - Computational linguistics
KW  - Mechanical Engineering
KW  - Engineering & Applied Sciences
KW  - Computer Science
KW  - Mechanical Engineering - General
KW  - NLP (Computer science)
KW  - Computer science.
KW  - Artificial intelligence.
KW  - Graph theory.
KW  - Computational linguistics.
KW  - Computer Science.
KW  - Artificial Intelligence (incl. Robotics).
KW  - Computational Linguistics.
KW  - Graph Theory.
KW  - Artificial intelligence
KW  - Electronic data processing
KW  - Human-computer interaction
KW  - Semantic computing
KW  - Artificial Intelligence.
KW  - Automatic language processing
KW  - Language and languages
KW  - Language data processing
KW  - Linguistics
KW  - Natural language processing (Linguistics)
KW  - Applied linguistics
KW  - Cross-language information retrieval
KW  - Mathematical linguistics
KW  - Multilingual computing
KW  - AI (Artificial intelligence)
KW  - Artificial thinking
KW  - Electronic brains
KW  - Intellectronics
KW  - Intelligence, Artificial
KW  - Intelligent machines
KW  - Machine intelligence
KW  - Thinking, Artificial
KW  - Bionics
KW  - Cognitive science
KW  - Digital computer simulation
KW  - Logic machines
KW  - Machine theory
KW  - Self-organizing systems
KW  - Simulation methods
KW  - Fifth generation computers
KW  - Neural computers
KW  - Data processing
KW  - Graph theory
KW  - Graphs, Theory of
KW  - Theory of graphs
KW  - Combinatorial analysis
KW  - Topology
KW  - Extremal problems
KW  - Natürliche Sprache.
KW  - Sprachverarbeitung.
KW  - Sprachdaten.
KW  - Mustererkennung.
KW  - Wortgraph.
KW  - Netzwerk.
KW  - Cluster-Analyse.
KW  - Graphentheorie.
UR  - https://www.unicat.be/uniCat?func=search&query=sysid:14302767
AB  - Current language technology is dominated by approaches that either enumerate a large set of rules, or are focused on a large amount of manually labelled data. The creation of both is time-consuming and expensive, which is commonly thought to be the reason why automated natural language understanding has still not made its way into “real-life” applications yet. This book sets an ambitious goal: to shift the development of language processing systems to a much more automated setting than previous works. A new approach is defined: what if computers analysed large samples of language data on their own, identifying structural regularities that perform the necessary abstractions and generalisations in order to better understand language in the process? After defining the framework of Structure Discovery and shedding light on the nature and the graphic structure of natural language data, several procedures are described that do exactly this: let the computer discover structures without supervision in order to boost the performance of language technology applications. Here, multilingual documents are sorted by language, word classes are identified, and semantic ambiguities are discovered and resolved without using a dictionary or other explicit human input. The book concludes with an outlook on the possibilities implied by this paradigm and sets the methods in perspective to human computer interaction. The target audience are academics on all levels (undergraduate and graduate students, lecturers and professors) working in the fields of natural language processing and computational linguistics, as well as natural language engineers who are seeking to improve their systems.  .
ER  -