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A Random Walk–Based Model for Identifying Semantic Orientation
Random Walk–Based Model Identifying Semantic Orientation
2015/9/14
Automatically identifying the sentiment polarity of words is a very important task that has been used as the essential building block of many natural language processing systems such as text classific...
Word Sense Disambiguation (WSD) systems automatically choose the intended meaning of a
word in context. In this article we present a WSD algorithm based on random walks over large
Lexical Knowledge ...
Connect-The-Dots: How many random points can a regular curve pass through?
Curve/Filament Detection. ε-Entropy Confi guration Functions
2015/8/21
Suppose n points are scattered uniformly at random in the unit square [0,1]2. Question:
How many of these points can possibly lie on some curve of length λ? Answer, proved here:
OP (λ ·
√n).
Toward a theory of information processing in graded,random,interactive networks
information processing in graded random interactive networks
2015/6/19
Toward a theory of information processing in graded,random,interactive networks.
Learning Random Walk Models for Inducing Word Dependency Distributions
Random Walk Models Inducing Word Dependency
2015/6/12
Many NLP tasks rely on accurately estimating word dependency probabilities P(w1|w2), where the words w1 and w2 have a particular relationship (such as verb-object). Because of the sparseness of counts...
A Conditional Random Field Word Segmenter for Sighan Bakeoff 2005
Conditional Random Field Word Segmenter Sighan Bakeoff 2005
2015/6/12
We present a Chinese word segmentation system submitted to the closed track of Sighan bakeoff 2005. Our segmenter was built using a conditional random field sequence model that provides a framework to...
REGULARIZATION, ADAPTATION, AND NON-INDEPENDENT FEATURES IMPROVE HIDDEN CONDITIONAL RANDOM FIELDS FOR PHONE CLASSIFICATION
Hidden Conditional Random Fields Speech Recognition Phone Classification Maximum a Posteriori
2015/6/12
We show a number of improvements in the use of Hidden Conditional Random Fields (HCRFs) for phone classification on the TIMIT and Switchboard corpora. We first show that the use of regularization effe...
Efficient, Feature-based, Conditional Random Field Parsing
Efficient Feature-based Conditional Random Field
2015/6/12
Discriminative feature-based methods are widely used in natural language processing, but sentence parsing is still dominated by generative methods. While prior feature-based dynamic programming parser...
A Conversational Movie Search System Based on Conditional Random Fields
conditional random fields spoken dialogue system
2015/3/9
Online streaming companies such as Netflix have become
dominant in the media distribution sector. However, such media
delivery services often support very rudimentary search,
especially for natu...
Random Walks on Context-Aware Relation Graphs for Ranking Social Tags
Context-Aware Relation Graphs Ranking Social Tags
2015/1/24
Random Walks on Context-Aware Relation Graphs for Ranking Social Tags.
A Hypercard Random Sentence Generator For Language Study
Hypercard Random Sentence Generator Language Study
2009/10/19
This is a description and explanation of a random sentence generator which can be used in the study of foreign languages. The paper explains in detail how to use the Hypercard stack Random Sentences. ...
A Uyghur Morpheme Analysis Method based on Conditional Random Fields
Xinjiang Uyghur Morpheme Agglutinative language CRFs Feature
2015/1/24
Morpheme analysis is very important for Uyghur language processing. Morpheme analysis
of Uyghur is quite different from other language, for this task the keys include feature
selection and the des...
A Uyghur Morpheme Analysis Method based on Conditional Random
A Uyghur Morpheme Analysis Method Conditional Random
2015/1/24
A Uyghur Morpheme Analysis Method based on Conditional Random.
Semi-supervised Learning for Image Annotation Based on Conditional Random Fields（图）
Image Annotation Conditional Random Fields
2015/1/24
Automatic image annotation (AIA) has been proved to be an effective and promising solution to automatically deduce the high-level semantics from low-level visual features. Due to the inherent ambiguit...