We have used different similarity measures to find the best method that increases the correctness. The present work is also credited through introduction of some new terms such as coefficient of efficiency, i.e., developer's ability and normalizer. In order to obtain the result, we have used ...
Minkowski Distance: It is a generic distance metric where Manhattan(r=1) or Euclidean(r=2) distance measures are generalizations of it. Manhattan Distance: It is the sum of absolute differences betw…
Similarity also plays a crucial role in support vector machines. Similarity assessment plays a key role in lazy learning methods such as k-nearest neighbor
In this work we address the task of computerassisted assessment of short student answers. We combine several graph alignment features with lexical semantic similarity measures using machine learning techniques and show that the student answers can be more accurately graded than if the semantic measures...
Entropy and similarity measure of Atanassov's intuitionistic fuzzy sets and their application to pattern recognition based on fuzzy measures In this study, we first examine entropy and similarity measure of Atanassov's intuitionistic fuzzy sets, and define a new entropy. Meanwhile, a constructio......
of similarity measures using machine learning, while keeping training time as low as possible. Our objective is to investigate how to apply machine learning to effectively learn a similarity measure. Such a learned similarity measure could be used for CBR systems, but also for clustering data in ...
Image similarity comparison simulating human perception (multiscale SSIM in Rust) cimage-benchmarksimilaritycomparisonlibpngcompress-imagessimilarity-measurementdssimssim UpdatedMar 5, 2025 Rust luozhouyang/python-string-similarity Star1k A library implementing different string similarity and distance measures us...
Similarity measures are typically used for quantifying the affinity between objects in search operations, in which the user presents an object (query) and requests other objects “similar” to the given query. Therefore, a similarity measure is a mathematical abstraction for comparing objects and it...
For each partition, we learn a different similarity measure: we apply machine learning techniques to combine a set of base similarity measures into an overall measure. To determine a good partitioning, we compare dif- ferent partitioning strategies. We achieved best results with a novel algorithm ...
Using these measures as features, it trains a support vector regression model on SemEval STS 2012 data. This model is then applied on the STS 2013 data to compute textual similarities. Two different selections of training data result in very different performance levels: while a cor- relation ...