In this paper, we apply an efficient top-k shortest distance routing algorithm to the link prediction problem and test its efficacy. We compare the results with other base line and state-of-the-art methods as well as with the shortest path. Our results show that using top-k distances as a similarity measure outperforms classical similarity measures such as Jaccard and Adamic/Adar.

When developing an index for a similarity search in metric spaces, how to divide the space for effective search pruning is a fundamental issue. We present Maximal Metric Margin Partitioning (MMMP), a partitioning scheme for similarity search indexes. MMMP divides the data based on its distribution pattern, especially for the boundaries of clusters. A partitioning boundary created by MMMP is lik...

We consider cluster structures in a general setting where they do not necessarily contain all singletons of the ground set. Then we provide a direct proof of the bijection between semi-proper robinsonian dissimilarities and indexed pre-pyramids. This result generalizes its analogue proven by Batbedat in the particular case of definite cluster structures. Moreover, the proposed proof shows that ...

Widespread interest in time-series similarity search has made more in need of efficient technique, which can reduce dimensionality of the data and then to index it easily using a multidimensional structure. In this paper, we introduce a technique, which we called grid representation, based on a grid approximation of the data. We propose a lower bounding distance measure that enables a bitmap ap...

We describe a class of measurable subsets Ω in R such that L2(Ω) has an orthogonal basis of frequencies eλ(x) = e i2πλ·x(x ∈ Ω) indexed by λ ∈ Λ ⊂ R. We show that such spectral pairs (Ω,Λ) have a self-similarity which may be used to generate associated fractal measures μ with Cantor set support. The Hilbert space L2(μ) does not have a total set of orthogonal frequencies, but a harmonic analysis...

A refined single-valued/interval neutrosophic set is very suitable for the expression and application of decision-making problems with both attributes and sub-attributes since it is described by its refined truth, indeterminacy, and falsity degrees. However, existing refined single-valued/interval neutrosophic similarity measures and their decision-making methods are scarcely studied in existin...

This paper proposes an efficient indexing mechanism for similarity search in highdimensional multimedia database that quickly filter-outs the irrelevant objects using a novel indexing structure, called HBI (Hierarchical Bitmap Index). In this bitmap index, the feature (or attribute) value of object at each dimension is represented with a set of two bits each of which indicates whether it is rel...

An information retrieval system employs a similarity heuristic to estimate the probability that documents and queries match each other. The heuristic is usually formulated in the context of a collection, so that the relationship between each document and the collection that contains it affects the scoring used to provide the ranked set of answers in response to a query. In this paper we continu...

Similarity has highly application dependent and even subjective characteristics. Similarity models therefore have to be adaptable to application specific requirements and individual user preferences. We focus on two aspects of adaptable similarity search: (1) Adaptable Similarity Models. Examples include pixelbased shape similarity as well as 2D and 3D shape histograms, applied to biomolecular ...