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Word sense induction using independent component analysis
... different word classes in the context and different sizes of feature ...the analysis, a hierarchical clustering is used to determine closeness of relation among feature vectors of specified ... See full document
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Soochow University: Description and Analysis of the Chinese Word Sense Induction System for CLP2010
... Word sense induction (WSI) is an open problem of natural language processing (NLP), which governs the process of automatic discovery of the possible senses of a ...to word sense ... See full document
6
Measuring the Impact of Sense Similarity on Word Sense Induction
... approaches: sense discrimi- nation degrades notably as the sense relatedness in- ...the analysis to different sense dis- tributions, varying number of senses, and for hu- man annotated ... See full document
11
Nonparametric Bayesian Word Sense Induction
... of sense cluters (Vlachos et ...when using a bag-of-words context model, in addition to allowing for variability in the number of senses across different words and ...labeled sense data was present, ... See full document
5
Word Sense Induction by Community Detection
... one sense also co-occur with terms correspond- ing to the other sense, ...ing sense-specific communities requires recognizing that the co-occurring terms may be shared by mul- tiple ... See full document
5
Word Sense Induction & Disambiguation Using Hierarchical Random Graphs
... of Weeds et al. (2004), who analyzed the variation in a word’s distributionally nearest neighbours with respect to a variety of similarity measures. Their analysis showed that there are three classes of mea- ... See full document
11
Word Independent Context Pair Classification Model for Word Sense Disambiguation
... Semantic Analysis based) trigger word similarity: LSA (Deerwester et ...By using the resulting ...each word can be represented as a vec- tor in the semantic ... See full document
7
One Million Sense Tagged Instances for Word Sense Disambiguation and Induction
... selected sense-tagged in- stances. Although the sense inventory is fine- grained (WordNet ...the sense-tag accuracy achieved is 83.7%. We also performed an error analysis to identify the ... See full document
7
A Sense Topic Model for Word Sense Induction with Unsupervised Data Enrichment
... enrichment) sense-topic model with S = 3 (row ...only using the single sentence of context given in each instance (while AI-KU and unimelb use large training sets from ...single sense. ... See full document
14
Unsupervised Word Sense Induction using Distributional Statistics
... Ontonotes sense inventory for the Gold Standard judgements, which are admitted even by the OntoNotes builders to be only 85% reliable on average (Hovy et ...standard word sense disam- biguation tasks ... See full document
9
Improving Word Sense Induction by Exploiting Semantic Relevance
... target word is represented by a vector of selected fea- tures ...contexts using semantically related but dis- tinct words will show no ...target word bank, which appears with one sense ...are ... See full document
5
Word Sense Induction with Neural biLM and Symmetric Patterns
... target word itself isn’t rep- resented in the ...stitutes word distribution representing the target word to take both kinds of information—the con- text as well as the target word—into ...the ... See full document
8
Combining Lexical Substitutes in Neural Word Sense Induction
... ous word in a particular context, also known as lexical contextual substitutes, are very helpful for WSI because possible substitutes strongly de- pend on the expressed meaning of the ambigu- ous ...the ... See full document
9
Using Pseudowords for Algorithm Comparison: An Evaluation Framework for Graph based Word Sense Induction
... monosemous word from the corresponding word graph should return only one cluster, and we would expect it to find exactly two clusters in the case of a pseudoword with two ... See full document
10
Which Noun Phrases Denote Which Concepts?
... a component for the Never-Ending Language Learner (NELL) (Carlson et ...both word sense induction and synonym resolution on relations extracted from text us- ing an ontology and a small amount ... See full document
11
Word Sense Induction using Cluster Ensemble
... make analysis through three facets: (a) to what extent feature selection can improve the clustering quality, (b) how much width of the smallest window that contains all the co–occurrence context can be reduced ... See full document
8
Taxonomy Learning Using Word Sense Induction
... The majority of taxonomy learning approaches are based on the distributional hypothesis (Harris, 1968). Typically, distributional similarity methods (Cimiano et al., 2004; Cimiano et al., 2005; Faure and N´edellec, 1998; ... See full document
9
Overview of the Chinese Word Sense Induction Task at CLP2010
... English word sense ...Chinese word sense induction (CWSI), in order to compare the performance of different Chinese WSI methods and find the methods which are suitable for the Chinese ... See full document
7
Iris Recognition Using Independent Component Analysis
... is using independent component analysis can produce spatially global ...method using integrodifferential operator. We use independent component analysis to generate ... See full document
5
Acoustic classification using independent component analysis
... nent analysis, and independent component ...for using the aforementioned techniques in modeling the human auditory system and its cognitive ...set using independent ... See full document
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