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 Knowledge Data Discovery. If we try to filter these data manually, it can take hours or days or months. So we need some interesting tool to access or retrieve the data for which data mining is used to mine that data an...

Because the data being mined in the temporal database will evolve with time, many researchers have focused on the incremental mining of frequent sequences in temporal database. In this paper, we propose an algorithm called IUS, using the frequent and negative border sequences in the original database for incremental sequence mining. To deal with the case where some data need to be updated from ...

Inquiry-based learning has been proposed as a natural and authentic way for students to engage with science. Inquiry-based learning environments typically require students to guide their own learning and inquiry processes as they gather data, make and test hypotheses and draw conclusions. Some students are highly self-regulated learners and are able to guide and monitor their own learning activ...

Data mining is an interactive and iterative process. It is very likely that a user will execute a series of similar queries differing in pattern constraints and mining parameters, before he or she gets satisfying results. Unfortunately, data mining algorithms currently available suffer from long processing times, which is unacceptable in case of interactive mining. In this paper we discuss effi...

This poster presents a sequence mining analysis of collaborative game-based learning for middle school computer science. Using pre-post test results, dyads were categorized into three groups based on learning gains. We then built first-order Markov models for the gameplay sequences. The models perform well for embedded assessment, classifying gameplay sequences with 95% accuracy according to wh...

E –learning is a method of learning that is delivered via electronic technology. Most of the E – Learning systems do not consider the individual aspects of the students ignoring the various requirements of the learners. Personalization is widely used in various fields to provide users with more suitable and personalized service. Personalization of E – Learning system is a method of improving th...

Mining data warehouses is still an open problem as few approaches really take into account the specifities of this framework (e.g. multidimensionnality, hierarchies, historized data). Multidimensional sequential patterns have been studied. However, they do not provide any way to handle hierarchies. In this paper, we propose an original method of extraction of sequential patterns taking into acc...

Feature extraction is the process of deriving new weakly correlated features from the original features in order to reduce the cost of feature measurement, increase classifier efficiency, and allows higher classification accuracy. The selection and quality of the features representing each pattern have considerable bearing on the success of subsequent pattern classification. In this paper, we s...

Optical pattern recognition under variations of illumination is an important issue. The sliced orthogonal nonlinear generalized (SONG) correlation has been proposed as an optical pattern recognition tool to discriminate with high efficiency between objects. But, at the same time, the SONG correlation is very sensitive to gray-scale image variations. In a previous work, we expanded the definitio...

Sequential pattern mining can prove to be very useful for predicating future activities, interpreting recurring phenomena, extracting similarities in a series of events, etc. For example, in the NASDAQ market, the problem of finding stocks whose closing prices are always about $ β0 higher than or β1 times the stocks of a given company, reduces to linear pattern retrieval: given query X , find a...