Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 74 for “"Part of speech"”.
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Part of speech N-grams for information retrieval
The increasing availability of information on the World Wide Web (Web), and the need to access relevant specs of this information provide an important impetus for the development of automatic intelligent Information Retrieval (IR) technology. IR systems convert human authored language into …
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Application of part-of-speech tagger in robust machine translation system
Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, June 2000.
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Data-driven Part-of-Speech taggers for Icelandic : comparison and error analysis
Part-of-Speech (POS) tagging is a sequential labelling task in which words, punctuation, and symbols occurring in running text, i.e., tokens are assigned a tag describing their morphosyntactic features. To predict the correct tag, the tagger relies on the context of the token in a sentence and its …
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Speaker Dependent Voice Recognition with Word-Tense Association and Part-of-Speech Tagging
<p>Extensive Research has been conducted on speech recognition and Speaker Recognition over the past few decades. Speaker recognition deals with identifying the speaker from multiple speakers and the ability to filter out the voice of an individual from the background for computational …
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Development of part of speech tagging and syntactic analysis software for Chinese text
Thesis (M.Eng. and S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, June 2001.
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Development of a tokenizer and rule-based part-of-speech tagger in Korean
Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.
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Automatic Lexicon Generation for Unsupervised Part-of-Speech Tagging Using Only Unannotated Text
With the growing number of textual resources available, the ability to understand them becomes critical. An essential first step in understanding these sources is the ability to identify the parts-of-speech in each sentence. The goal of this research is to propose, improve, and implement an …
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Part-of-speech tagging and partial parsing for Irish using finite-state transducers and constraint grammar
… we present the development and evaluation of a suite of annotation tools for unrestricted Irish text, which go from tokenization, morphological analysis, part-of-speech tagging, right through to partial parsing. In order to develop such tools, a large body of texts is required for testing …
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The effects of part–of–speech tagging on text–to–speech synthesis for resource–scarce languages
In the world of human language technology, resource-scarce languages (RSLs) suffer from the problem of little available electronic data and linguistic expertise. The Lwazi project in South Africa is a large-scale endeavour to collect and apply such resources for all eleven of the official South …
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Comparing incidental learning of nouns and verbs using eye movements
It has long been assumed that people learn much of their vocabulary incidentally during the course of natural reading. Prior research has identified a host of factors that affect the ease or likelihood of learning a new word from written context. Findings from various areas of cognitive science …
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The Application of P-Bar Theory in Transformation-Based Error-Driven Learning
… a rule based method for determining the context of a partext (i.e., a part of a text document). </p> <p>In <em>Transformation-Based Error-Driven Learning and Natural Language Processing: A Case Study in Part-of-Speech Tagging </em>Brill (1995) demonstrates a method of error-driven learning …
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Machine Learning for Information Extraction
The dissertation presents a number of novel machine learning techniques and applies them to information extraction. The study addresses several information extraction subtasks: part of speech tagging, entity extraction, coreference resolution, and relation extraction. Each of the tasks is …
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Multi-Class Classification in Natural Language Processing
… and empirical arguments for the advantages of using: (i) Sentence structure. (ii) The Sequential Model . Empirical arguments are given using word-prediction and part of speech tagging tasks. Theoretical arguments present this thesis as an extension of the current classification methods which …
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Multi-source domain adaptation with mixture of experts
We propose a mixture-of-experts approach for unsupervised domain adaptation from multiple sources. The key idea is to explicitly capture the relationship between a target example and different source domains. This relationship, expressed by a point-to-set metric, determines how to combine …
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A morphological-syntactical analysis approach for Arabic textual tagging
Part-of-Speech (POS) tagging is the process of labeling or classifying each word in written text with its grammatical category or part-of-speech, i.e. noun, verb, preposition, adjective, etc. It is the most common disambiguation process in the field of Natural Language Processing (NLP). POS tagging …
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Integrating source-language context into log-linear models of statistical machine translation
The translation features typically used in state-of-the-art statistical machine translation (SMT) model dependencies between the source and target phrases, but not among the phrases in the source language themselves. A swathe of research has demonstrated that integrating source context modelling …
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Unsupervised multilingual learning
… languages. In this thesis, we present a class of probabilistic models that exploit these links as a form of naturally occurring supervision. These models allow us to substantially improve performance for core text processing tasks, such as morphological segmentation, part-of-speech tagging, and …
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Representation and learning schemes for sentiment analysis.
This thesis identifies four novel techniques of improving the performance of sentiment analysis of text systems. Thes include feature extraction and selection, enrichment of the document representation and exploitation of the ordinal structure of rating classes. The techniques were evaluated on …
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Learning multiple solutions to computer vision problems
… [1, 2, 3, 4, 5, 6, 7] has led to a resurgence of deep learning methods in computer vision. Deep learning techniques have since led to tremendous successes in the field of computer vision. Some of the prominent ones are the progress made on the problems of image classification [8, 9, 10], image …
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