MelodyShape is a Java library and tool to compute the melodic similarity between monophonic music pieces. It implements several algorithms that compute similarity based on the geometric shape that melodies describe in the pitch-time plane. All these algorithms have obtained the best results in the MIREX Symbolic Melodic Similarity task in 2010, 2011, 2012, 2013, 2014 and 2015 editions, as well ...

In this paper, we focus on similarity searching for similar acoustic data over unstructured decentralised P2P networks. Similarity is measured in terms of time warping, which can cope with distortion that is naturally present when query-by-content is performed. We propose a novel framework, which takes advantage of the absence of overhead in unstructured P2P networks and minimises the required ...

Ontology similarity calculation and ontology mapping are crucial research topics in information retrieval. Ontology, as a concept structure model, is widely used in biology, physics, geography and social sciences. In this paper, we present new algorithms for ontology similarity measurement and ontology mapping using harmonic analysis and diffusion regularization on hypergraph. The optimal funct...

Relative similarity learning (RSL) aims to learn similarity functions from data with relative constraints. Most previous algorithms developed for RSL are batch-based learning approaches which suffer from poor scalability when dealing with realworld data arriving sequentially. These methods are often designed to learn a single similarity function for a specific task. Therefore, they may be sub-o...

In machine learning problems, labeled data are often in short supply. One of the feasible solution for this problem is transfer learning. It can make use of the labeled data from other domain to discriminate those unlabeled data in the target domain. In this paper, we propose a transfer learning framework based on similarity matrix approximation to tackle such problems. Two practical algorithms...

We introduce a new view-based object representation , called the saliency map graph (SMG), which captures the salient regions of an object view at multiple scales using a wavelet transform. This compact representation is highly invariant to translation, rotation, and scaling, and ooers the locality of representation required for occluded object recognition. We then introduce two graph similarit...

The clustering of biological sequence data is a significant task for biologists. The reason is that sequence clustering assists molecular biologists to group sequences based on the ancestral traits or hereditary information that are hidden in sequences. To accomplish the similarity detection and clustering tasks, several clustering algorithms, similarity and distance measures have been proposed...

Searching documents that are similar to a query document is an important component in modern information retrieval. Some existing hashing methods can be used for efficient document similarity search. However, unsupervised hashing methods cannot incorporate prior knowledge for better hashing. Although some supervised hashing methods can derive effective hash functions from prior knowledge, they ...

This article presents effective (dynamic) algorithm for solving a problem of counting the number of substrings of given string which are also substrings of second string. Presented algorithm can be used for example for quick calculation of strings similarity measure using generalized ngram method (Niewiadomski measure [2]), which are shown. Correctness and complexity analyses are included. 1 Oz...

We calculate the scaling behavior of the second-kind self-similar blow-up solution of an aggregation equation in odd dimensions. This solution describes the radially symmetric finite-time blowup phenomena and has been observed in numerical simulations of the dynamic problem. The nonlocal equation for the self-similar profile is transformed into a system of ODEs that is solved using a shooting m...