Defines the notion of an activity model learned from sensor data and presents key
algorithms that form the core of the field Activity Learning: Discovering, Recognizing and …

A task of sequential pattern generation can be considered as a problem which is inverse to
sequential pattern mining. This paper presents two novel approaches to the sequential …

Discovering sequential pattern from a large sequence database is an important problem in
the field of sequential pattern mining, which is the well-known data mining technique …

Finding frequent sequential patterns has been defined as finding ordered list of items that
occur more times in a database than a user defined threshold. For big and dense databases …

Sequential pattern mining is a fundamental and essential field of data mining because of its
extensive scope of applications spanning from the forecasting the user shopping patterns …

A lot of database is available in the world which is to be screened to find out various facts
such as history of symptoms from which disease can be diagnosed, accessing data from …

Similarity based stream time series is gaining ever-increasing attention due to its importance
in many applications such as financial data processing, network monitoring, Web click …

In this paper, we argue on and we prove constructively that considering significance and
support in a hand to find sequential patterns can be solved more efficiently than the original …

Indonesia is one of the most disaster prone countries in the world. The country faces multiple
hazards such as earthquakes, tsunami, volcanic eruptions, floods, landslides, drought, and …