Topic taxonomies, which represent the latent topic (or category) structure of document
collections, provide valuable knowledge of contents in many applications such as web …

Anomaly detection (AD) is a fast growing and popular domain among established
applications like vision and time series. We observe a rich literature for these applications …

Anomaly detection is the problem of identifying unusual patterns in data. This problem is
relevant for a wide variety of applications in various domains such as fault and damage …

The detection of outliers in text documents is a highly challenging task, primarily due to the
unstructured nature of documents and the curse of dimensionality. Text document outliers …

Identifying outlier documents, whose content is different from the majority of the documents
in a corpus, has played an important role to manage a large text collection. However, due to …

Machine learning answers to the problem of handling dedicated tasks with a wide variety of
data. Such algorithms can be either simple or difficult to handle depending of the data. Low …

This systematic literature review synthesized 64 studies from 2017–2023 to analyze recent
advances in anomalous text detection methods and applications. The analysis revealed …

El objetivo de este estudio es incrementar la eficacia del proceso de análisis y la objetividad
de las decisiones en la evaluación final y mostrar la calidad de los trabajos de investigación …

La tâche de détection des données aberrantes consiste à étudier un ensemble de données
afin d'estimer les individus singuliers. Cette tâche est souvent effectuée pour supprimer le …

Data Mining–known as the process of extracting knowledge from massive data sets–leads to
phenomenal impacts on our society, and now affects nearly every aspect of our lives: from …