Calculating the semantic similarity between sentences is a long dealt problem in the area of natural language processing. The semantic analysis field has a crucial role to play in the research related to the text analytics. The semantic similarity differs as the domain of operation differs. In this paper, we present a methodology which deals with this issue by incorporating semantic similarity ...

WordNet::Similarity is a freely available software package that makes it possible to measure the semantic similarity and relatedness between a pair of concepts (or synsets). It provides six measures of similarity, and three measures of relatedness, all of which are based on the lexical database WordNet. These measures are implemented as Perl modules which take as input two concepts, and return ...

To compensate for the common inability of people with lexical production impairments to access and express intended concepts, we make use of models of human semantic memory that build on the notion of semantic similarity and relatedness. Such models, constructed on evidence gained from psycholinguistic experiments, form the basis of a large lexical database, WORDNET. We augment WORDNET with man...

In this paper we demonstrate a system that automatically annotates text documents with a given domain ontology’s concepts. The annotation process utilizes lexical and Web resources to analyze the semantic similarity of text components with any of the ontology concepts, and outputs a list with the proposed annotations, accompanied with appropriate confidence values. The demonstrated system is av...

Most text processing systems need to compare lexical units – words, entities, semantic concepts – with each other as a basic processing step within large and complex systems. A significant amount of research has taken place in formulating and evaluating multiple similarity metrics, primarily between words. Often, such techniques are resourceintensive or are applicable only to specific use cases...

Lexical co-occurrence counts from large corpora have been used to construct highdimensional vector-space models of language.. Distances between word vectors extracted from these models are generally considered to reflect semantic similarity. Implicit in this assumption is that ‘semantic distance’ measurements correspond to human intuitions. This paper investigates the validity of one such measu...

In this paper, we introduce a framework that identifies online plagiarism by exploiting lexical, syntactic and semantic features that includes duplication-gram, reordering and alignment of words, POS and phrase tags, and semantic similarity of sentences. We establish an ensemble framework to combine the predictions of each model. Results demonstrate that our system can not only find considerabl...

The issue of sentence semantic similarity is important and essential to many applications of Natural Language Processing. This issue was treated in some frameworks dealing with the similarity between short texts especially with the similarity between sentence pairs. However, the semantic component was paradoxically weak in the proposed methods. In order to address this weakness, we propose in t...

This paper suggests a method for detecting cross-lingual semantic similarity using parallel PropBanks. We begin by improving word alignments for verb predicates generated by GIZA++ by using information available in parallel PropBanks. We applied the Kuhn-Munkres method to measure predicateargument matching and improved verb predicate alignments by an F-score of 12.6%. Using the enhanced word al...

WordNet is a large lexical database of English language, in which, nouns, verbs, adjectives, and adverbs are grouped into sets of cognitive synonyms (synsets). Each synset expresses a distinct concept. Synsets are interlinked by both semantic and lexical relations. WordNet is essentially used for word sense disambiguation, information retrieval, and text translation. In this paper, we propose s...