17 citations · 26 across the 7 of their papers we have counts for
7 papers
RankSum An unsupervised extractive text summarization based on rank fusion
A. Joshi, E. Fidalgo, E. Alegre +1
In this paper, we propose Ranksum, an approach for extractive text summarization of single documents based on the rank fusion of four multi-dimensional sentence features extracted…
Classifying spam emails using agglomerative hierarchical clustering and a topic-based approach
F. Janez-Martino, R. Alaiz-Rodriguez, V. Gonzalez-Castro +2
Spam emails are unsolicited, annoying and sometimes harmful messages which may contain malware, phishing or hoaxes. Unlike most studies that address the design of efficient anti-sp…
Short Text Classification Approach to Identify Child Sexual Exploitation Material
Mhd Wesam Al-Nabki, Eduardo Fidalgo, Enrique Alegre +1
Producing or sharing Child Sexual Exploitation Material (CSEM) is a serious crime fought vigorously by Law Enforcement Agencies (LEAs). When an LEA seizes a computer from a potenti…
Classification of Spam Emails through Hierarchical Clustering and Supervised Learning
Francisco Jáñez-Martino, Eduardo Fidalgo, Santiago González-Martínez +1
Spammers take advantage of email popularity to send indiscriminately unsolicited emails. Although researchers and organizations continuously develop anti-spam filters based on bina…
Evaluating Performance of an Adult Pornography Classifier for Child Sexual Abuse Detection
Mhd Wesam Al-Nabki, Eduardo Fidalgo, Roberto A. Vasco-Carofilis +2
The information technology revolution has facilitated reaching pornographic material for everyone, including minors who are the most vulnerable in case they were abused. Accuracy a…
Improving Named Entity Recognition in Tor Darknet with Local Distance Neighbor Feature
Mhd Wesam Al-Nabki, Francisco Jañez-Martino, Roberto A. Vasco-Carofilis +2
Name entity recognition in noisy user-generated texts is a difficult task usually enhanced by incorporating an external resource of information, such as gazetteers. However, gazett…
Content-Based Features to Rank Influential Hidden Services of the Tor Darknet
Mhd Wesam Al-Nabki, Eduardo Fidalgo, Enrique Alegre +1
The unevenness importance of criminal activities in the onion domains of the Tor Darknet and the different levels of their appeal to the end-user make them tangled to measure their…