We present larger-scale evidence overturning previous results, showing that among the many alternative phrasal lexical similarity measures based on word vectors, the Jaccard coefficient most increases the robustness of MEANT, the recently introduced, fully-automatic, state-of-the-art semantic MT evaluation metric. MEANT critically depends on phrasal lexical similarity scores in order to automat...

Ipomoea genus is widely distributed in the tropical and subtropical regions of the world. The exploration of genetic diversity is pre-requisite for genome organization in the wild species and the related domesticated ones. Inter-simple Sequence Repeat (ISSR) markers was used to assess the identification of 21 important Ipomoea species and determination of the genetic relationships among these s...

Semantic similarity measures play an important role in the extraction of semantic relations. Semantic similarity measures are widely used in Natural Language Processing (NLP) and Information Retrieval (IR). The work proposed here uses web based metrics to compute the semantic similarity between words or terms and also compares with the state-of-the-art. For a computer to decide the semantic sim...

Similarity measures are essential to solve many pattern recognition problems such as classification, clustering, and retrieval problems. Various similarity measures are categorized in both syntactic and semantic relationships. In this paper we present a novel similarity, Unilateral Jaccard Similarity Coefficient (uJaccard), which doesn’t only take into consideration the space among two points b...

Despite several decades of research into segmentation techniques, unsupervised medical image segmentation is barely usable in a clinical context, and still at vast user time expense. The Fast Marching method is an established segmentation technique for generic spaces, which typically requires manual initialisation. This paper illustrates unsupervised organ segmentation through the use of a nove...

Establishing accurate genetic similarity and dissimilarity between individuals is an essential and decisive point for clustering and analyzing inter and intra population diversity because different similarity and dissimilarity indices may yield contradictory outcomes. We assessed the variations caused by three commonly used similarity coefficients including Jaccard, Sorensen-Dice and Simple mat...

Semantic similarity has become an important tool and widely been used to solve traditional Information Retrieval problems. This study adopts ontology of computer science and proposes an ontology indexing weight based on Wu and Palmer’s edge counting measure and uses the N-grams method for computing a family of word similarity. The study also compares the subsumption weight between Hliaoutakis a...

With the rapid growth of neuroimaging research and accumulation of neuroinformatic databases the synthesis of consensus findings using meta-analysis is becoming increasingly important. Meta-analyses pool data across many studies to identify reliable experimental effects and characterize the degree of agreement across studies. Coordinate-based meta-analysis (CBMA) methods are the standard approa...