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PREDICTING DEVELOPMENT OF RESEARCH IN MUSIC BASED ON
PREDICTING DEVELOPMENT OF RESEARCH IN MUSIC BASED ON

... shallow parsing with mining on textual data gives much better results than simple DM. NLP techniques are also being injected to Information Retrieval increasing performance of this systems. Finally, the great improvement has been done in machine translation, the first goal of NLP researchers, where ...
Semi-Supervised Approach to Named Entity Recognition in Spanish
Semi-Supervised Approach to Named Entity Recognition in Spanish

... We propose an implementation of the Viterbi algorithm to tag every word in a conversation with a realworld dialog system. The resulting HMM corresponds to an observed output w1 , w2 , . . . , wT (the words in a conversation), and the states y1 , y2 , . . . , yT (the POS-tags for each word). Some sim ...
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Intro to (psycho)linguistics and n-gram models

... • Learning and processing biases reflect existing structure. ...
Biological computation: amazing algorithms. Nature
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Development of a Ligand Knowledge Base

... Compile systematic structural information about TM complexes ...
Lecture 2: Re-thinking Representation: Meaning
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Learning to Parse Database Queries Using Inductive
Learning to Parse Database Queries Using Inductive

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Challenges in Computational Modeling of Affective Processes
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... Theorem: Let S be a set of n line segments in the plane. All intersection points in S, with for each intersection point the segments involved in it, can be reported in O(n log n + k log n) time and O(n) space, where k is the size of the output.. ...
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FinalReview08 - Columbia University
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... develops from structures, processes, and “idea”which are in the mind at birth (i.e. are innate), rather than from the environment, and that these are responsible for the basic structure of language and how it is learned.  This hypothesis has been used to explain how children are able to learn langu ...
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Keynotes - IEEE Computer Society

... improved significantly by the use of artificial neural networks (ANN), such as deep feedforward multilayer perceptrons and recurrent neural networks (incl. long short-term memory extension). In addition, from the architectural point of view, there are a number of novel concepts like CTC (connectioni ...
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Computational linguistics

Computational linguistics is an interdisciplinary field concerned with the statistical or rule-based modeling of natural language from a computational perspective.Traditionally, computational linguistics was usually performed by computer scientists who had specialized in the application of computers to the processing of a natural language. Computational linguists often work as members of interdisciplinary teams, including linguists (specifically trained in linguistics), language experts (persons with some level of ability in the languages relevant to a given project), and computer scientists. In general, computational linguistics draws upon the involvement of linguists, computer scientists, experts in artificial intelligence, mathematicians, logicians, philosophers, cognitive scientists, cognitive psychologists, psycholinguists, anthropologists and neuroscientists, among others.Computational linguistics has theoretical and applied components, where theoretical computational linguistics takes up issues in theoretical linguistics and cognitive science, and applied computational linguistics focuses on the practical outcome of modeling human language use.
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