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Semantic similarity assessment of words using weighted WordNet
Word and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. Word-Net, as a popular concept hierarchy, is used in many such applications. ...
Weighted Semantic Similarity Assessment Using WordNet
—Word and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. WordNet, as a popular concept hierarchy, is used in many such applications. ...
Weighted Semantic Similarity Assessment Using WordNet
—Word and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. WordNet, as a popular concept hierarchy, is used in many such applications. ...
Using WordNet to determine semantic similarity of words
Word and concept similarity assessment is one of the most important elements in natural language processing and information and knowledge retrieval. WordNet, as a popular concept hierarchy, is used in many such applications. ...
Learning parameters of fuzzy Bayesian Network based on imprecise observations
In recent years, Bayesian Network has become an important modeling method for decision making problems of realworld applications. In this paper learning parameters of a fuzzy Bayesian Network (BN) based on imprecise/fuzzy ...
فضای جدید مبتنی بر انطباق منحنی جهت طبقه بندی داده ها
در این مقاله یک فضای جدید مبتنی بر انطباق منحنی (CFS) جهت نگاشت داده های جداپذیر غیرخطی به داده های جداپذیر خطی ارائه گردیده است. نگاشتهای کوادراتیک یا خطی ،داده ها را به فضای جدید به گونه ای نگاشت می دهند که طبقه بندی ...
Curve fitting space for classification
Abstract In this paper, a curve fitting space (CFS) is
presented to map non-linearly separable data to linearly
separable ones. A linear or quadratic transformation maps
data into a new space for better ...
Shell fitting space for classification
In this paper, a shell fitting space (SFS) is presented to map non-linearly separable data to linearly separable
ones. A linear or quadratic transformation maps data into a new space for better classification, ...