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Article
1D Multi-Point Local Ternary Pattern: A Novel Feature Extraction Method for Analyzing Cognitive Engagement of students in Flipped Learning Pedagogy
Flipped learning is a blended learning method based on academic engagement of students online (outside class) and offline (inside class). In this learning pedagogy, students receive lesson any time from lectur...
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Article
Inferencing transportation mode using unsupervised deep learning approach exploiting GPS point-level characteristics
Discovering the mode of transportation is a fundamental and challenging step in the various transportation analysis problems such as travel demand analysis, transport planning, and traffic management. Supervis...
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Chapter and Conference Paper
Accelerating LOF Outlier Detection Approach
Outliers are the deformities in the data that diverges from the normal behavior. Detection of outlier points is a crucial task as it leads to the extraction of the discordant observations in different domains....
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Article
RDPOD: an unsupervised approach for outlier detection
Outliers are the data points which deviate significantly from the majority of the data points. Finding outliers is an important task in various applications, especially in data mining. The unsupervised techniq...
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Chapter and Conference Paper
User Preference Multi-criteria Recommendations Using Neural Collaborative Filtering Methods
with a single rating provided by a user on an item. However, in many domains such as tourism, hotels, etc., a user would love to give rating for every criterion of an item based on his several experienc...
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Chapter and Conference Paper
A Hybrid Framework for Improving Diversity and Long Tail Items in Recommendations
In today’s information overloaded era, recommender system is a necessity and it is widely used in most of the domains of e-commerce. Over the years, recommender system is improved to meet the main purpose of a...
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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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Chapter and Conference Paper
Reduction in Execution Cost of k-Nearest Neighbor Based Outlier Detection Method
Outlier detection is an important task as it leads to the discovery of critical information in a variety of the application domains. The variants of k-nearest neighbor based outlier detection method have been suc...
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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
Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data
Collaborative Filtering (CF) is one of the most successful approaches for personalized product recommendations. Neighborhood based collaborative filtering is an important class of CF, which is simple and effic...
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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
Tolerance Rough Set Theory Based Data Summarization for Clustering Large Datasets
Finding clusters in large datasets is an interesting challenge in many fields of Science and Technology. Many clustering methods have been successfully developed over the years. However, most of the existing c...
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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...
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Chapter and Conference Paper
Fast Single-Link Clustering Method Based on Tolerance Rough Set Model
The single-link (SL) clustering method is not scalable with the size of the dataset and needs many database scans. This is potentially a severe problem for large datasets. One way to speed up the SL method is ...
