Learning document representation is important in applying machine learning algorithms for
sentiment analysis. Distributed representation learning models of words and documents …

Wild flowers and plants play an important role in protecting biodiversity and providing
various ecosystem services. However, some of them are endangered or threatened and are …

With the aim of analyzing large-sized multidimensional single-cell datasets, we are
describing a method for Cosine-based Tanimoto similarity-refined graph for community …

Tanimoto, or extended Jaccard, is an important similarity measure which has seen
prominent use in fields such as data mining and chemoinformatics. Many of the existing …

Similarity query is the family of queries based on some similarity metrics. Unlike the
traditional database queries which are mostly based on value equality, similarity queries aim …

Extreme multi-label classification problems occur in different applications such as prediction
of tags or advertisements. We propose a new algorithm that predicts labels using a linear …

Similarity join on high‐dimensional data is a primitive operation. It is used to find all data
pairs that with distance no more than ϵ from the given data set according to a specific …

In this paper, we proposed a method for plant classification, which aims to recognize the
type of leaves from a set of image instances captured from same viewpoints. Firstly, for …

The nearest neighbor graph is an important structure in many data mining methods for
clustering, advertising, recommender systems, and outlier detection. Constructing the graph …

Traditional collaborative filtering recommender systems need to retrain the entire dataset in
case of drastic data changes, which generates huge computational overhead in big data …