Multi-label learning deals with data associated with multiple labels simultaneously. Previous work on multi-label learning assumes that for each instance, the "full" lab...
Change impact analysis aims at identifying software artifacts being affected by a change. In the past, this problem has been addressed by approaches relying on static, dynamic, a...
Michele Ceccarelli, Luigi Cerulo, Gerardo Canfora,...
The widespread use of templates on the Web is considered harmful for two main reasons. Not only do they compromise the relevance judgment of many web IR and web mining methods suc...
Karane Vieira, Altigran Soares da Silva, Nick Pint...
Effective system verification requires good specifications. The lack of sufficient specifications can lead to misses of critical bugs, design re-spins, and time-to-market slips. I...
Discovery of frequent patterns has been studied in a variety of data mining settings. In its simplest form, known from association rule mining, the task is to discover all frequent...