|
|
|
Luca Cagliero, Lorenzo Canale and Laura Farinetti
Computer laboratories are learning environments where students learn programming languages by practicing under teaching assistants? supervision. This paper presents the outcomes of a real case study carried out in our university in the context of a datab...
ver más
|
|
|
|
|
|
|
Christie I. Ezeife and Hemni Karlapalepu
E-commerce recommendation systems usually deal with massive customer sequential databases, such as historical purchase or click stream sequences. Recommendation systems? accuracy can be improved if complex sequential patterns of user purchase behavior ar...
ver más
|
|
|
|
|
|
|
Eric Hsueh-Chan Lu and You-Ru Lin
With the rise in the Internet of Things (IOT), mobile devices and Location-Based Social Network (LBSN), abundant trajectory data have made research on location prediction more popular. The check-in data shared through LBSN hide information related to lif...
ver más
|
|
|
|
|
|
|
Amira Abdelwahab and Nesma Youssef
Data mining techniques are useful in discovering hidden knowledge from large databases. One of its common techniques is sequential rule mining. A sequential rule (SR) helps in finding all sequential rules that achieved support and confidence threshold fo...
ver más
|
|
|
|
|
|
|
Diego Santoro, Andrea Tonon and Fabio Vandin
Sequential pattern mining is a fundamental data mining task with application in several domains. We study two variants of this task?the first is the extraction of frequent sequential patterns, whose frequency in a dataset of sequential transactions is hi...
ver más
|
|
|
|
|
|
|
Andrea Brunello, Enrico Marzano, Angelo Montanari and Guido Sciavicco
Temporal information plays a very important role in many analysis tasks, and can be encoded in at least two different ways. It can be modeled by discrete sequences of events as, for example, in the business intelligence domain, with the aim of tracking t...
ver más
|
|
|
|
|
|
|
Yutika Amelia Effendi,Nania Nuzulita
Pág. 183 - 194
Background: Nowadays, enterprise computing manages business processes which has grown up rapidly. This situation triggers the production of a massive event log. One type of event log is double timestamp event log. The double timestamp has a start time an...
ver más
|
|
|
|
|
|
|
Xinglong Yuan, Wenbing Chang, Shenghan Zhou and Yang Cheng
Sequential pattern mining (SPM) is an effective and important method for analyzing time series. This paper proposed a SPM algorithm to mine fault sequential patterns in text data. Because the structure of text data is poor and there are many different fo...
ver más
|
|
|
|
|
|
|
Edona Doko,Lejla Abazi Bexheti,Mentor Hamiti,Blerta Prevalla Etemi
Pág. pp. 109 - 122
The paper aim is to come up with methodology for performing video learning data history of learner?s video watching logs, video segments or time series data in accordance with learning processes via mobile technologies. To reach this goal, it is introduc...
ver más
|
|
|
|