Matches in SemOpenAlex for { <https://semopenalex.org/work/W4247245408> ?p ?o ?g. }
Showing items 1 to 69 of
69
with 100 items per page.
- W4247245408 abstract "The text document classification tasks passes under the Automatic Classification (also known as pattern Recognition) problem in Machine Learning and Text Mining. It is necessary to classify large text documents into specific classes, to make clear and search simply. Classified data are easy for users to browse. The important issue in usual text document classification is representing the features for classification of an unknown document into predefined categories. The Combination of classifiers is fused together to increase the accuracy classification result in a single text document. This paper states a novel fusion approach to classify text documents by considering ES-VSM and Bigram representation models for text documents. ES-VSM: Enhanced Sentence –Vector Space Model is an advanced feature of the sentence based vector space model and extension to simple VSM will be considered for the constructive representation of text documents. The main objective of the study is to boost the accuracy of text classification by accounting for the features extracted from the text document. The proposed system concatenates two different representation models of the text documents for designing two different classifiers and feeds them as one input to the classifier. An enhanced S-VSM and interval-valued representation model are considered for the effective representation of text documents. A word level neural network Bigram representation of text documents is proposed for effective capturing of semantic information present in the text data. A Proposed approach improves the overall accuracy of text document classification to a significant extent. Keywords: ES-VSM; Fusion, Text Document Classification, Neural Network, Text Representation, Machine learning. DOI: 10.7176/NMMC/93-03 Publication date: September 30 th 2020" @default.
- W4247245408 created "2022-05-12" @default.
- W4247245408 date "2020-09-01" @default.
- W4247245408 modified "2023-10-17" @default.
- W4247245408 title "Text Document Categorization using Enhanced Sentence Vector Space Model and Bi-Gram Text Representation Model Based on Novel Fusion Techniques" @default.
- W4247245408 doi "https://doi.org/10.7176/nmmc/93-03" @default.
- W4247245408 hasPublicationYear "2020" @default.
- W4247245408 type Work @default.
- W4247245408 citedByCount "0" @default.
- W4247245408 crossrefType "journal-article" @default.
- W4247245408 hasBestOaLocation W42472454081 @default.
- W4247245408 hasConcept C108757681 @default.
- W4247245408 hasConcept C117884012 @default.
- W4247245408 hasConcept C137293760 @default.
- W4247245408 hasConcept C137546455 @default.
- W4247245408 hasConcept C153180895 @default.
- W4247245408 hasConcept C154945302 @default.
- W4247245408 hasConcept C17744445 @default.
- W4247245408 hasConcept C199539241 @default.
- W4247245408 hasConcept C204321447 @default.
- W4247245408 hasConcept C23123220 @default.
- W4247245408 hasConcept C2776359362 @default.
- W4247245408 hasConcept C2777530160 @default.
- W4247245408 hasConcept C2780479914 @default.
- W4247245408 hasConcept C41008148 @default.
- W4247245408 hasConcept C66945725 @default.
- W4247245408 hasConcept C71472368 @default.
- W4247245408 hasConcept C81363708 @default.
- W4247245408 hasConcept C83665646 @default.
- W4247245408 hasConcept C89686163 @default.
- W4247245408 hasConcept C94625758 @default.
- W4247245408 hasConcept C95623464 @default.
- W4247245408 hasConceptScore W4247245408C108757681 @default.
- W4247245408 hasConceptScore W4247245408C117884012 @default.
- W4247245408 hasConceptScore W4247245408C137293760 @default.
- W4247245408 hasConceptScore W4247245408C137546455 @default.
- W4247245408 hasConceptScore W4247245408C153180895 @default.
- W4247245408 hasConceptScore W4247245408C154945302 @default.
- W4247245408 hasConceptScore W4247245408C17744445 @default.
- W4247245408 hasConceptScore W4247245408C199539241 @default.
- W4247245408 hasConceptScore W4247245408C204321447 @default.
- W4247245408 hasConceptScore W4247245408C23123220 @default.
- W4247245408 hasConceptScore W4247245408C2776359362 @default.
- W4247245408 hasConceptScore W4247245408C2777530160 @default.
- W4247245408 hasConceptScore W4247245408C2780479914 @default.
- W4247245408 hasConceptScore W4247245408C41008148 @default.
- W4247245408 hasConceptScore W4247245408C66945725 @default.
- W4247245408 hasConceptScore W4247245408C71472368 @default.
- W4247245408 hasConceptScore W4247245408C81363708 @default.
- W4247245408 hasConceptScore W4247245408C83665646 @default.
- W4247245408 hasConceptScore W4247245408C89686163 @default.
- W4247245408 hasConceptScore W4247245408C94625758 @default.
- W4247245408 hasConceptScore W4247245408C95623464 @default.
- W4247245408 hasLocation W42472454081 @default.
- W4247245408 hasOpenAccess W4247245408 @default.
- W4247245408 hasPrimaryLocation W42472454081 @default.
- W4247245408 hasRelatedWork W2029157577 @default.
- W4247245408 hasRelatedWork W2160451891 @default.
- W4247245408 hasRelatedWork W2163264304 @default.
- W4247245408 hasRelatedWork W2168805572 @default.
- W4247245408 hasRelatedWork W2275058042 @default.
- W4247245408 hasRelatedWork W2811311845 @default.
- W4247245408 hasRelatedWork W2995914718 @default.
- W4247245408 hasRelatedWork W3090877066 @default.
- W4247245408 hasRelatedWork W3145957033 @default.
- W4247245408 hasRelatedWork W564581980 @default.
- W4247245408 isParatext "false" @default.
- W4247245408 isRetracted "false" @default.
- W4247245408 workType "article" @default.