7 Result(s)
within
Bidyut Kr. Patra
Information Systems Applications (incl. Internet)
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Article
Hidden location prediction using check-in patterns in location-based social networks
Check-in facility in a location-based social network (LBSN) enables people to share location information as well as real-life activities. Analysing these historical series of check-ins to predict the future lo...
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Chapter and Conference Paper
An Incremental Approach for Collaborative Filtering in Streaming Scenarios
The crux of a recommendation engine is to process users ratings and provide personalized suggestions to the user. However, processing the ratings and providing recommendations in real time still remains challe...
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Article
Effective data summarization for hierarchical clustering in large datasets
Cluster analysis in a large dataset is an interesting challenge in many fields of Science and Engineering. One important clustering approach is hierarchical clustering, which outputs hierarchical (nested) stru...
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Chapter and Conference Paper
Distance based Incremental Clustering for Mining Clusters of Arbitrary Shapes
Clustering has been recognized as one of the important tasks in data mining. One important class of clustering is distance based method. To reduce the computational and storage burden of the classical clusteri...
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Chapter and Conference Paper
Neighborhood Based Clustering Method for Arbitrary Shaped Clusters
Discovering clusters of arbitrary shape with variable densities is an interesting challenge in many fields of science and technology. There are few clustering methods, which can detect clusters of arbitrary sh...
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Chapter and Conference Paper
NDoT: Nearest Neighbor Distance Based Outlier Detection Technique
In this paper, we propose a nearest neighbor based outlier detection algorithm, NDoT. We introduce a parameter termed as $ Nearest \mb...
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Chapter and Conference Paper
Distance Based Fast Hierarchical Clustering Method for Large Datasets
Average-link (AL) is a distance based hierarchical clustering method, which is not sensitive to the noisy patterns. However, like all hierarchical clustering methods AL also needs to scan the dataset many time...
