The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
The largeness and the heterogeneity of most graph-modeled datasets in several database application areas make the query process a real challenge because of the lack of a complete ...
Federica Mandreoli, Riccardo Martoglia, Giorgio Vi...
This paper addresses the problem of Named Entity Recognition in Query (NERQ), which involves detection of the named entity in a given query and classification of the named entity...
The volume of spam e-mails has grown rapidly in the last two years resulting in increasing costs to users, network operators, and e-mail service providers (ESPs). E-mail users dem...