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Multilingual Metaphor Processing: Experiments with Semi-Supervised and Unsupervised Learning
Semi-Supervised Unsupervised Learning
2017/4/6
Highly frequent in language and communication, metaphor represents a significant challenge
for Natural Language Processing (NLP) applications. Computational work on metaphor has
traditionally evolve...
This article proposes ESA, a new unsupervised approach to word segmentation. ESA is an iterative process consisting of 3 phases: Evaluation, Selection, and Adjustment. In Evaluation, both certainty an...
This article surveys work on Unsupervised Learning of Morphology. We define Unsupervised
Learning of Morphology as the problem of inducing a description (of some kind, even if only
morpheme se...
The Noisy Channel Model for Unsupervised Word Sense Disambiguation
Word Sense Disambiguation Noisy Channel Model
2015/9/8
We introduce a generative probabilistic model, the noisy channel model, for unsupervised word
sense disambiguation. In our model, each context C is modeled as a distinct channel through
which the sp...
Unsupervised Type and Token Identification of Idiomatic Expressions
Unsupervised Type Token Identification Idiomatic Expressions
2015/9/7
Idiomatic expressions are plentiful in everyday language, yet they remain mysterious, as it is not clear exactly how people learn and understand them. They are of special interest to linguists, psycho...
There has been a great deal of recent research into word sense disambiguation, particularly since the inception of the Senseval evaluation exercises. Because a word often has more than one meaning, re...
Unsupervised Multilingual Sentence Boundary Detection
Unsupervised Multilingual Sentence Boundary Detection
2015/9/1
In this article, we present a language-independent, unsupervised approach to sentence boundary detection. It is based on the assumption that a large number of ambiguities in the determination of sente...
Unsupervised Learning of the Morphology of a Natural Language
Unsupervised Learning Natural Language
2015/8/26
This study reports the results of using minimum description length (MDL) analysis to model unsupervised learning of the morphological segmentation of European languages, using corpora ranging in size ...
Unsupervised Named Entity Recognition Using Syntactic and Semantic Contextual Evidence
Unsupervised Named Entity Recognition Syntactic Semantic Contextual
2015/8/26
Proper nouns form an open class, making the incompleteness of manually or automatically learned classification rules an obvious problem. The purpose of this paper is twofold: first, to suggest the use...
Modeling Unsupervised Perceptual Category Learning
human learning mixture of Gaussians online learning unsupervised learning
2015/6/23
During the learning of speech sounds and other perceptual categories, category labels are not provided, the number of categories is unknown, and the stimuli are encountered sequentially. These constra...
Unsupervised Learning of Field Segmentation Models for Information Extraction
Unsupervised Learning Field Segmentation Models Information Extraction
2015/6/12
The applicability of many current information extraction techniques is severely limited by the need for supervised training data. We demonstrate that for certain field structured extraction tasks, suc...
Unsupervised Discovery of a Statistical Verb Lexicon
Unsupervised Statistical Verb Lexicon
2015/6/12
This paper demonstrates how unsupervised techniques can be used to learn models of deep linguistic structure. Determining the semantic roles of a verb’s dependents is an important step in natural lang...
Punctuation:Making a Point in Unsupervised Dependency Parsing
Punctuation Unsupervised Dependency Parsing
2015/6/10
We show how punctuation can be used to improve unsupervised dependency parsing. Our linguistic analysis confirms the strong connection between English punctuation and phrase boundaries in the Penn Tre...
Lateen EM: Unsupervised Training with Multiple Objectives,Applied to Dependency Grammar Induction
Lateen EM Unsupervised Training Multiple Objectives Dependency Grammar Induction
2015/6/10
We present new training methods that aim to mitigate local optima and slow convergence in unsupervised training by using additional imperfect objectives. In its simplest form, lateen EM alternates bet...
Unsupervised Dependency Parsing without Gold Part-of-Speech Tags
Unsupervised Dependency Parsing Gold Part Speech Tags
2015/6/10
We show that categories induced by unsupervised word clustering can surpass the performance of gold part-of-speech tags in dependency grammar induction. Unlike classic clustering algorithms, our metho...