Semantic relatedness between words has been successfully extracted from navigation on Wikipedia pages. However, the navigational data used in the corresponding works are sparse and expected to be biased since they have been collected in the context of games. In this paper, we raise this limitation and explore if semantic relatedness can also be extracted from unconstrained navigation. To this e...

Memory for emotional items is often better than memory for neutral items. In three experiments, we examined whether this typical finding is due to the higher semantic relatedness inherent to emotional items, a confound in previous studies. We also controlled for other possible confounding variables, such as imagery. In Experiments 1 and 2, participants encoded lists of emotional and categorized...

This paper provides a comparative analysis of the performance of four state-of-the-art distributional semantic models (DSMs) over 11 languages, contrasting the native language-specific models with the use of machine translation over English-based DSMs. The experimental results show that there is a significant improvement (average of 16.7% for the Spearman correlation) by using state-of-the-art ...

In the multi-label classification setting, documents can be labelled with a number of concepts (instead of just one). Evaluating the performance of classifiers in this scenario is often as simple as measuring the percentage of correctly assigned concepts. Classifiers that do not retrieve a single concept existing in the ground truth annotation are all considered equally poor. However, some clas...

Lexical Semantic Relatedness and Its Application in Natural Language Processing Alexander Budanitsky Department of Computer Science University of Toronto August 1999 A great variety of Natural Language Processing tasks, from word sense disambiguation to text summarization to speech recognition, rely heavily on the ability to measure semantic relatedness or distance between words of a natural la...

A divided visual field (DVF) experiment examined the semantic processing strategies employed by the cerebral hemispheres to determine if strategies observed with written word stimuli generalize to other media for communicating semantic information. We employed picture stimuli and vary the degree of semantic relatedness between the picture pairs. Participants made an on-line semantic relatedness...

This paper proposes a new image-semantic measure, named "Semantico-Visual Relatedness of Concepts" (SVRC ), to estimate the semantic similarity between concepts. The proposed measure incorporates visual, conceptual and contextual information to provide a measure which is more meaningful and more representative of image semantics. We also propose a new methodology to automatically build a semant...

Wikipedia provides an enormous amount of background knowledge to reason about the semantic relatedness between two entities. We propose Wikipedia-based Distributional Semantics for Entity Relatedness (DiSER), which represents the semantics of an entity by its distribution in the high dimensional concept space derived from Wikipedia. DiSER measures the semantic relatedness between two entities b...

The emergence of knowledge repositories in a variety of domains provides a valuable opportunity for semantic interpretation of high dimensional datasets. Previous researches investigate the use of concept instead of word as a core semantic feature for incorporating semantic knowledge from an ontology into the representation model of documents. On the other hand, in machine learning and informat...

The emergence of knowledge repositories in a variety of domains provides a valuable opportunity for semantic interpretation of high dimensional data sets. Previous researches investigate the use of concept instead of word as a core semantic feature for incorporating semantic knowledge from an ontology into the representation model of documents. On the other hand, in machine learning and informa...