In recent years a variety of approaches in computing semantic relatedness have been proposed. However, the algorithms and resources employed differ strongly, as well as the results obtained under different experimental conditions. This article investigates the quality of various semantic relatedness measures in a comparative study. We conducted an extensive experiment using a broad variety of m...

This paper presents an alternative method to measuring word-word semantic relatedness in distributional semantics framework. The main idea is to represent target words as rankings of all co-occurring words in a text corpus, ordered by their tf – idf weight and use a metric between rankings (such as Jaro distance or Rank distance) to compute semantic relatedness. This method has several advantag...

Code similarity is a central challenge in many programming related applications, such as code search, automatic translation, and plagiarism detection. In this work, we reduce the problem of semantic relatedness between code fragments into a problem of semantic relatedness of textual descriptions. Our main idea is that we can use the relationship between code and its textual descriptions as esta...

A great variety of tasks, from word sense disambiguation and document retrieval to assessing the functional similarity of gene products and validating protein-protein interaction networks, depend on the ability to measure the semantic similarity between concepts organized in ontologies. This report is a comprehensive study of classic and recent computational methods measuring semantic relatedne...

When thousands of vocabularies having been published on the Semantic Web by various authorities, a question arises as to how they are related to each other. Existing work has mainly analyzed their similarity. In this paper, we inspect the more general notion of relatedness, and characterize it from four angles: well-defined semantic relatedness, lexical similarity in contents, closeness in expr...

This paper presents our work on using the graph structure of Wiktionary for synonym detection. We implement semantic relatedness metrics using both a direct measure of information flow on the graph and a comparison of the list of vertices found to be “close” to a given vertex. Our algorithms, evaluated on ESL 50, TOEFL 80 and RDWP 300 data sets, perform better than or comparable to existing sem...

In five experiments, we extended the production effect-better memory for items said aloud than for items read silently-to paired-associate learning, the goal being to explore whether production enhances associative information in addition to enhancing item information. In Experiments 1 and 2, we used a semantic-relatedness task in addition to the production manipulation and found no evidence of...

Measuring semantic relatedness between words or concepts is a crucial process to many Natural Language Processing tasks. Exiting methods exploit semantic evidence from a single knowledge source, and are predominantly evaluated only in the general domain. This paper introduces a method of harnessing different knowledge sources under a uniform model for measuring semantic relatedness between word...

The recognition of conversational speech is a hard problem. Semantic relatedness measures can improve speech recognition performance when using contextual information, as Demetriou [5] has shown. The standard n-gram approach in language modeling for speech recognition cannot cope with long distance dependencies [4]. Therefore J. Bellegarda [2] proposed combining n-gram language models, which ar...

Related words/concepts prime one another, but the notion of semantic relatedness is notoriously difficult to pin down and may be due to linguistic association (reflecting the likelihood of two words appearing in shared/similar contexts) and/or true semantic overlap (reflecting how similar two words are in conceptual representation). In the present work, we propose a novel measure of semantic re...