The issue of authorship attribution has long been considered and continues to be a popular
topic. Because of advances in digital computers, this field has experienced rapid …

Causal relation extraction is a challenging yet very important task for Natural Language
Processing (NLP). There are many existing approaches developed to tackle this task, either …

Authorship analysis (AA) is the study of unveiling the hidden properties of authors from
textual data. It extracts an author's identity and sociolinguistic characteristics based on the …

The authorship of questioned documents often constitutes important evidence in criminal
and civil cases. Linguistic stylistic analysis can often help to determine authorship …

The Authorship Attribution (AA) is considered as a subfield of authorship analysis and it is an
important problem as the range of anonymous information increased with fast-growing of …

" Contract cheating," instances in which a student enlists someone other than themselves to
produce coursework, has been identified as a growing problem within academic integrity …

Recently, document embeddings methods have been proposed aiming at capturing hidden
properties of the texts. These methods allow to represent documents in terms of fixed-length …

This is a new substantially revised edition of the book, where we discuss the use of syntactic
information (represented as syntactic n-grams) in the tasks of computational linguistics …

An interesting model to represent texts as a graph (also called network) is the word
adjacency (co-occurrence) representation, which is known to capture mainly syntactical …

In computational authorship attribution (AA)–the task of identifying the author of a given text
based on a set of possible candidates–existing differences across domains, languages or …