Motif: A malware reference dataset with ground truth family labels
Malware family classification is a significant issue with public safety and research
implications that has been hindered by the high cost of expert labels. The vast majority of …
implications that has been hindered by the high cost of expert labels. The vast majority of …
CBET: design and evaluation of a domain-specific chatbot for mobile learning
Q Liu, J Huang, L Wu, K Zhu, S Ba - Universal Access in the Information …, 2020 - Springer
The popularity of mobile devices and conversational agents in recent years has seen wide
use of chatbots in different educational scenarios. In relation to the advances in mobile …
use of chatbots in different educational scenarios. In relation to the advances in mobile …
A comparative study of sequential minimal optimization-based support vector machines, vote feature intervals, and logistic regression in landslide susceptibility …
Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region
of Himalaya (India) with the objective of comparing the predictive capability of three different …
of Himalaya (India) with the objective of comparing the predictive capability of three different …
Specialty detection in the context of telemedicine in a highly imbalanced multi-class distribution
The Covid-19 pandemic has led to an increase in the awareness of and demand for
telemedicine services, resulting in a need for automating the process and relying on …
telemedicine services, resulting in a need for automating the process and relying on …
Syntactically aware neural architectures for definition extraction
Automatically identifying definitional knowledge in text corpora (Definition Extraction or DE)
is an important task with direct applications in, among others, Automatic Glossary …
is an important task with direct applications in, among others, Automatic Glossary …
BCGAN: A CGAN-based over-sampling model using the boundary class for data balancing
A class imbalance problem occurs when a dataset is decomposed into one majority class
and one minority class. This problem is critical in the machine learning domains because it …
and one minority class. This problem is critical in the machine learning domains because it …
Multilingual SMS-based author profiling: Data and methods
In the recent years, many benchmark author profiling corpora have been developed for
various genres including Twitter, social media, blogs, hotel reviews and e-mail, etc …
various genres including Twitter, social media, blogs, hotel reviews and e-mail, etc …
Improving voting feature intervals for spatial prediction of landslides
In this study, the main aim is to improve performance of the voting feature intervals (VFIs),
which is one of the most effective machine learning models, using two robust ensemble …
which is one of the most effective machine learning models, using two robust ensemble …
Definition extraction with lstm recurrent neural networks
SL Li, B Xu, TL Chung - … on Natural Language Processing Based on …, 2016 - Springer
Definition extraction is the task to identify definitional sentences automatically from
unstructured text. The task can be used in the aspects of ontology generation, relation …
unstructured text. The task can be used in the aspects of ontology generation, relation …
Applying dependency relations to definition extraction
Definition Extraction (DE) is the task to automatically identify definitional knowledge in
naturally-occurring text. This task has applications in ontology generation, glossary creation …
naturally-occurring text. This task has applications in ontology generation, glossary creation …