Introduction: The purpose of multimodal and co-registration In MR Neuroimaging is to fuse two or more sets images (T1, T2, fMRI, DTI, pMRI, …) for combining the different information into a composite correlated data set in order to visualization, re-alignment and generating transform to functional Matrix. Multimodal registration and motion correction in spinal cord MR Neuroimag...

Recent studies have shown that graph-based approaches are effective for semi-supervised learning. The key idea behind many graph-based approaches is to enforce the consistency between the class assignment of unlabeled examples and the pairwise similarity between examples. One major limitation with most graph-based approaches is that they are unable to explore dissimilarity or negative similarit...

Good similarity functions are crucial for many important subtasks in data integration, such as “soft joins” and data deduping, and one widely-used similarity function is TFIDF similarity. In this paper we describe a modification of TFIDF similarity that is more appropriate for certain datasets: namely, large data collections formed by merging together many smaller collections, each of which is ...

Recently, social recommendation becomes a hot research direction, which leverages social relations among users to alleviate data sparsity and cold-start problems in recommender systems. The social recommendation methods usually employ simple similarity information of users as social regularization on users. Unfortunately, the widely used social regularization may suffer from several aspects: (1...

Good similarity functions are crucial for many important subtasks in data integration, such as “soft joins” and data deduping, and one widely-used similarity function is TFIDF similarity. In this paper we describe a modification of TFIDF similarity that is more appropriate for certain datasets: namely, large data collections formed by merging together many smaller collections, each of which is ...

Commonly to classify new object in Data Mining one should estimate its similarity with given classes. Function of Rival Similarity (FRiS) is assigned to calculate quantitative measure of similarity considering a competitive situation. FRiS-function allows constructing new effective algorithms for various Data Mining tasks solving. In particular, it enables to obtain quantitative estimation of c...