[PDF][PDF] A review of machine learning algorithms for text-documents classification
With the increasing availability of electronic documents and the rapid growth of the World
Wide Web, the task of automatic categorization of documents became the key method for …
Wide Web, the task of automatic categorization of documents became the key method for …
The impact of deep learning on document classification using semantically rich representations
This paper presents a semantically rich document representation model for automatically
classifying financial documents into predefined categories utilizing deep learning. The …
classifying financial documents into predefined categories utilizing deep learning. The …
Learning document representation via topic-enhanced LSTM model
W Zhang, Y Li, S Wang - Knowledge-Based Systems, 2019 - Elsevier
Document representation plays an important role in the fields of text mining, natural
language processing, and information retrieval. Traditional approaches to document …
language processing, and information retrieval. Traditional approaches to document …
Latent association rule cluster based model to extract topics for classification and recommendation applications
FF dos Santos, MA Domingues… - Expert Systems with …, 2018 - Elsevier
The quality of any text mining technique is highly dependent on the features that are used to
represent the document collection. A classical form of document representation is the vector …
represent the document collection. A classical form of document representation is the vector …
Novel term weighting schemes for document representation based on ranking of terms and Fuzzy logic with semantic relationship of terms
Weighting and normalization are the most important factor that may affect the text
representation significantly. This paper presents two novel term weighting schemes to …
representation significantly. This paper presents two novel term weighting schemes to …
[HTML][HTML] Performance analysis of machine learning classifiers on improved concept vector space models
Z Kastrati, AS Imran - Future Generation Computer Systems, 2019 - Elsevier
This paper provides a comprehensive performance analysis of parametric and non-
parametric machine learning classifiers including a deep feed-forward multi-layer …
parametric machine learning classifiers including a deep feed-forward multi-layer …
[PDF][PDF] An overview of e-documents classification
A Khan, BB Bahurdin, K Khan - 2009 International Conference on …, 2011 - academia.edu
With the increasing availability of electronic documents and the rapid growth of the World
Wide Web, the task of automatic categorization of documents becomes the key method for …
Wide Web, the task of automatic categorization of documents becomes the key method for …
Semantically-grounded construction of centroids for datasets with textual attributes
Centroids are key components in many data analysis algorithms such as clustering or
microaggregation. They are considered as the central value that minimises the distance to …
microaggregation. They are considered as the central value that minimises the distance to …
[图书][B] Library classification trends in the 21st century
R Kumbhar - 2011 - books.google.com
Library Classification Trends in the 21st Century traces development in and around library
classification as reported in literature published in the first decade of the 21st century. It …
classification as reported in literature published in the first decade of the 21st century. It …
An improved concept vector space model for ontology based classification
This paper proposes an improved concept vector space (ICVS) model which takes into
account the importance of ontology concepts. Concept importance shows how important a …
account the importance of ontology concepts. Concept importance shows how important a …