Large network analysis is a very important topic in data mining. A significant body of work in the area studies the problem of node similarity. One way to express node similarity is to associate with each node the set of 1-hop neighbors and compute the Jaccard similarity between these sets. This information can be used subsequently for more complex operations like link prediction, clustering or...

In decision making, similarity measure and distance between two objects are crucial to be able to determine the relationship between those objects. Many researchers have received much attention for their research on this subject. In this study, we propose two novel similarity measures between hesitant fuzzy linguistic term sets (HFLTSs). In addition, two extensions of Technique for Order of Pre...

In this work, we filter weakly expressed genes using the HTSFilter Bioconductor package, which implements a databased filtering procedure based on the calculation of a global Jaccard similarity index among biological replicates for read counts arising from replicated transcriptome sequencing (RNA-seq) data; see Rau et al. (2013) and the HTSFilter vignette for additional details. This technique ...

The Exact Set Similarity Join problem aims to find all similar sets between two collections of sets, with respect to a threshold and a similarity function such as overlap, Jaccard, dice or cosine. The näıve approach verifies all pairs of sets and it is often considered impractical due the high number of combinations. So, Exact Set Similarity Join algorithms are usually based on the Filter-Verif...

The biological importance of rhizosphere sediment-associated fungi in mangroves is poorly understood, especially when they are affected by high salinity and anaerobiosis disturbed areas. This study evaluated the fungal diversity sediments three mangrove species associated with conservation conditions forests preserved, semi-preserved, deteriorated In addition, bioactivity was correlated to foun...

Text categorization is one of the well studied problems in data mining and information retrieval. Given a large quantity of documents in a data set where each document is associated with its corresponding category. Categorization involves building a model from classified documents, in order to classify previously unseen documents as accurately as possible. In this paper, we investigate variatio...

This paper presents a comparison between two image segmentation approaches based on background subtraction and supervised learning. Real images from two important issues, which have been studied by several computer vision research groups, were used in our experiments: namely, sign language interpretation and mouse behavior classification. According to performance measures, such as accurate rate...

genetic diversity relationships of 50 isolates of cytospora schulzeri on apple from different parts of the semirom region were analyzed using 15 polymerase chain reaction (pcr) based markers, 7 random amplified polymorphic dnas (rapds) and 8 microsatellite primed polymerase chain reaction (mp-pcr). using 7 selected rapd primers 113 bands were generated, of which 81 bands were polymorphic (71.7%...

Accurately delineating the brain on magnetic resonance (MR) images of the head is a prerequisite for many neuroimaging methods. Most existing methods exhibit disadvantages in that they are laborious, yield inconsistent results, and/or require training data to closely match the data to be processed. Here, we present pincram, an automatic, versatile method for accurately labelling the adult brain...

There has been a significant increase from 2010 to 2016 in the number of people suffering from spine problems. The automatic image segmentation of the spine obtained from a computed tomography (CT) image is important for diagnosing spine conditions and for performing surgery with computer-assisted surgery systems. The spine has a complex anatomy that consists of 33 vertebrae, 23 intervertebral ...