Abstract The Cluster Validity Index is an integral part of clustering algorithms. It evaluates
inter-cluster separation and intra-cluster cohesion of candidate clusters to determine the …

Abstract This work presents Hybrid Capuchin Search Algorithm (HCSA) as a meta-heuristic
method to deal with the vexing problems of local optima traps and initialization sensitivity of …

Abstract Density Peak Clustering (DPC) is a popular state-of-the-art clustering algorithm,
which requires pairwise (dis) similarity of data objects to detect arbitrary shaped clusters …

Social media platforms such as Twitter or StockTwits are widely used for sharing stock
market opinions between investors, traders, and entrepreneurs. Empirically, previous work …

A limitation of many probabilistic topic models such as Latent Dirichlet Allocation (LDA) is
their inflexibility to use local contexts. As a result, these models cannot directly benefit from …

This paper proposes a novel mask-based output layer for multi-level hierarchical
classification, addressing the limitations of existing methods which (i) often do not embed the …

This paper presents Marine-tree, a large-scale hierarchical annotated dataset for marine
organism classification. Marine-tree contains more than 160k annotated images divided into …

Twitter represents a massively distributed information source over topics ranging from social
and political events to entertainment and sports news. While recent work has suggested this …

Clustering is a powerful and extensively used data science tool. While clustering is generally
thought of as an unsupervised learning technique, there are also supervised variations such …

The information retrieval behavior of scientific researchers is a behavior that is affected by
multiple factors such as cognition, emotion, task, and user type and has its unique cognitive …