Computing the semantic similarity between words is one of the key challenges in many language-based applications. Previous work tends to use the contextual information of words to disclose the degree of their similarity. In this paper, we consider the relationships between words in local contexts as well as latent topic information of words to propose a new distributed representation of words f...

In Distributional Semantic Models (DSMs), Vector Cosine is widely used to estimate similarity between word vectors, although this measure was noticed to suffer from several shortcomings. The recent literature has proposed other methods which attempt to mitigate such biases. In this paper, we intend to investigate APSyn, a measure that computes the extent of the intersection between the most ass...

In this paper, we propose an algebraic similarity measure σBS (BS stands for BitSim) for assigning semantic similarity score to concept definitions in ALCH+ an expressive fragment of Description Logics (DL). We define an algebraic interpretation function, IB, that maps a concept-definition to a unique string (ωB) (called bit-code) over an alphabet ∑ B of 11 symbols belonging to LB the language ...

In this paper, we consider the problem of finding the k most similar objects given a query object, in large multimedia datasets. We focus on scenarios where the similarity measure itself is not fixed, but is continuously being refined with user feedback. Conventional database techniques for efficient similarity search are not effective in this environment as they take a specific similarity/dist...

This article presents two case studies to explore whether and how web corpora can be used to automatically acquire lexical-semantic knowledge from distributional information. For this purpose, we compare three German web corpora and a traditional newspaper corpus on modelling two types of semantic relatedness: (1) Assuming that free word associations are semantically related to their stimuli, w...

This article evaluates the similarity of images of natural textures with changes of scale and rotation, through the application of structural metrics. The applied metrics are: Complex-Wavelet Structural Similarity Metric (CW-SSIM) and Structural Texture Similarity Metric (STSIM). First a decomposition of the images in sub-bands was realized. With the generated information the descriptors were e...

Reasoning by analogy is essential to provide new conclusions helpful to solve a problem. Here we present the definition of a new operator aimed at reasoning by analogy. The proposed reasoner relies on the Roles Mapping Engine. It finds analogous roles encoded in descriptions that use domain-specific terminology, overcoming syntactical constraints that limit the relations to have the same name. ...

Thread disentanglement is the task of separating out conversations whose thread structure is implicit, distorted, or lost. In this paper, we perform email thread disentanglement through pairwise classification, using text similarity measures on non-quoted texts in emails. We show that i) content text similarity metrics outperform style and structure text similarity metrics in both a class-balan...

Computing the similarity between data elements is a basic functionality in flexible query answering systems. In the case of complex data definitions, for instance in terms of an ontology, computing the similarity between data elements becomes a non-trivial problem. In this paper, we propose a similarity measure for data described in terms of the DL-lite ontology language. In this measure, we ta...

We suggest a variation of the Hellerstein— Koutsoupias—Papadimitriou indexability model for datasets equipped with a similarity measure, with the aim of better understanding the structure of indexing schemes for similarity-based search and the geometry of similarity workloads. This in particular provides a unified approach to a great variety of schemes used to index into metric spaces and facil...