Text preprocessing is often the first step in the pipeline of a Natural Language Processing
(NLP) system, with potential impact in its final performance. Despite its importance, text …

In this paper, we consider the task of text categorization as a graph classification problem.
By representing textual documents as graph-of-words instead of historical n-gram bag-of …

A standard approach to Information Retrieval (IR) is to model text as a bag of words.
Alternatively, text can be modelled as a graph, whose vertices represent words, and whose …

ABSTRACT A common and standard approach to model text document is bag-of-words. This
model is suitable for capturing word frequency, however structural and semantic information …

Text classification is an important problem with many applications. Traditional approaches
represent text as a bag-of-words and build classifiers based on this representation. Rather …

Currently, there is a large amount of text being shared through the Internet. These texts are
available in different forms—structured, unstructured and semi structured. There are different …

Software-Defined Networking (SDN) is an emerging technology, physically separating data
and control planes of network devices. From a security point of view SDN has two sides …

Text categorization is an important task with plenty of applications, ranging from sentiment
analysis to automated news classification. In this paper, we introduce a novel graph-based …

In this paper, we present a novel document similarity measure based on the definition of a
graph kernel between pairs of documents. The proposed measure takes into account both …

Word co-occurrence networks have been employed to analyze texts both in the practical and
theoretical scenarios. Despite the relative success in several applications, traditional co …