Temporal data is one of the most common form of data in internet of things. Data from
various sources such as sensors, smart phones, smart homes and smart vehicles in near …

Over the years, a large amount of temporal data needs to be shared and exchanged on the
Web. Resource Description Framework (RDF) has been widely accepted and has rapidly …

Mining temporal association patterns from time-stamped temporal databases, first
introduced in 2009, remain an active area of research. A pattern is temporally similar when it …

Mining periodic patterns in time series databases is a daunting research task that plays a
significant role at decision making in real life applications. There are many algorithms for …

Time profiled association mining is one of the important and challenging research problems
that is relatively less addressed. Time profiled association mining has two main challenges …

Mining association patterns from a time-stamped temporal database is implicitly associated
with task of scanning input database. Finding supports of itemsets requires scanning the …

Spatio-temporal data serves as a foundation for most location-based applications
nowadays. To handle spatio-temporal data, an appropriate methodology needs to be …

Discovery of temporal association patterns from temporal databases is extensively studied
by academic research community and applied in various industrial applications. Temporal …

Abstract Mining Temporal Patterns from temporal databases is challenging as it requires
handling efficient database scan. A pattern is temporally similar when it satisfies subset …

Support values of itemsets in snapshot databases are existence probability of itemsets at a
single time slot. A time-stamped transaction (temporal) database may be viewed as a …