In this study, we propose a method for encoding documents into string vectors, instead of
numerical vectors. A traditional approach to text categorization usually requires encoding …

This research proposes a new neural network for text categorization which uses alternative
representations of documents to numerical vectors. Since the proposed neural network is …

We consider the problem of text representation and categorization. Conventionally, a text
document is represented by a vector in high dimensional space. Some learning algorithms …

Text categorization is used to automatically assign previously unseen documents to a
predefined set of categories. This paper gives a short introduction into text categorization …

In recent years, text categorization based on machine learning is a widely used technology
in the field of information retrieval and text mining and has gained many advances. This …

Text categorization is the task of assigning predefined categories to natural language text.
With the widely used'bag of words' representation, previous researches usually assign a …

Text categorization is the task of classifying natural language documents into a set of
predefine categories. Documents are typically represented by sparse vectors under the …

There are three factors involved in text classification. These are classification model,
similarity measure and document representation model. In this paper, we will focus on …

Automatic text categorization has always been an important application and research topic
since the inception of digital documents. Today, text categorization is a necessity due to the …

Text categorization presents unique challenges to traditional classification methods due to
the large number of features inherent in the datasets from real-world applications of text …