A WordNet-based Semantic Similarity Measure Enhanced by Internet-based Knowledge
نویسندگان
چکیده
Approaches for measuring semantic similarity between words have been widely employed in various areas such as Artificial Intelligence, Linguistics, Cognitive Science and Knowledge Engineering. A new semantic similarity measure is proposed in this paper, which exploits the knowledge retrieved from a semantic network (i.e., WordNet) and the Internet. In particular, the structure information from WordNet and the statistic information obtained from the Internet are combined to quantify the semantic similarity between words. The new similarity measure is evaluated by comparing the rating results with two sets of human benchmark data. Experimental results indicate that, the proposed similarity measure outperforms previous WordNet-based semantic similarity measures. Keywords-semantic similarity; WordNet; Normalised Google Distance
منابع مشابه
Automatic Construction of Persian ICT WordNet using Princeton WordNet
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...
متن کاملDERI&UPM: Pushing Corpus Based Relatedness to Similarity: Shared Task System Description
In this paper, we describe our system submitted for the semantic textual similarity (STS) task at SemEval 2012. We implemented two approaches to calculate the degree of similarity between two sentences. First approach combines corpus-based semantic relatedness measure over the whole sentence with the knowledge-based semantic similarity scores obtained for the words falling under the same syntac...
متن کاملEstimation of Semantic Similarity between Concepts using Multiple Ontologies (Wordnet and Mesh) FOR Biomedical DATA
The majority of the intelligent knowledge-based applications include elements for the purpose of measuring semantic similarity stuck between terms. A lot of the available semantic similarity measures that make use of ontology structure as their chief source cannot determine semantic similarity among terms and concepts by means of multiple ontologies. Hence, this research looks for a new approac...
متن کاملMahtab at SemEval-2017 Task 2: Combination of Corpus-based and Knowledge-based Methods to Measure Semantic Word Similarity
In this paper, we describe our proposed method for measuring semantic similarity for a given pair of words at SemEval2017 monolingual semantic word similarity task. We use a combination of knowledge-based and corpus-based techniques. We use FarsNet, the Persian WordNet, besides deep learning techniques to extract the similarity of words. We evaluated our proposed approach on Persian (Farsi) tes...
متن کاملAn improved semantic similarity measure for document clustering based on topic maps
A major computational burden, while performing document clustering, is the calculation of similarity measure between a pair of documents. Similarity measure is a function that assigns a real number between 0 and 1 to a pair of documents, depending upon the degree of similarity between them. A value of zero means that the documents are completely dissimilar whereas a value of one indicates that ...
متن کامل