Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

Nowadays, in the international scientific community of machine learning, there exists an
enormous discussion about the use of black-box models or explainable models; especially …

Ontology learning, particularly axiom learning, is a challenging task that focuses on building
expressive and decidable ontologies. The literature proposes several research efforts aimed …

Preventing and detecting intrusions and attacks on wireless networks has become an
important and serious challenge. On the other hand, due to the limited resources of wireless …

Event popularity prediction over social media is crucial for estimating information
propagation scope, decision making, and emergency prevention. However, existing …

Events are occurrences in specific locations, time, and semantics that nontrivially impact
either our society or the nature, such as earthquakes, civil unrest, system failures …

Event prediction is a challenging task which is controversial and highly debatable in the
area of text mining. Previous works in utilizing causality reasoning for event prediction have …

Sentiment analysis is a process through which the beliefs, sentiments, allusions, behaviors,
and tendencies in a written language are analyzed using Natural Language Processing …

Event prediction is the ability of anticipating future events, ie, future real-world occurrences,
and aims to support the user in deciding on actions that change future events towards a …

Data clustering is one of the most important tasks of data mining. This paper aims to
describe an integrated data clustering method based on Imperialist Competitive Algorithm …