BibTeX:

@article{IJIRSTV3I12083,
     title={A Survey on Semantic Similarity Measures},
     author={Aditi Gupta, Mr. Ajay Kumar and Dr. Jyoti Gautam},
     journal={International Journal for Innovative Research in Science & Technology},
     volume={3},
     number={12},
     pages={243--247},
     year={},
     url={http://www.ijirst.org/articles/IJIRSTV3I12083.pdf},
     publisher={IJIRST (International Journal for Innovative Research in Science & Technology)},
}

Measuring the semantic similarity between words, sentences and concepts is an important task in information retrieval, document clustering, web mining and word sense disambiguation. Semantic similarity is basically a measure used to compute the extent of similarity between two concepts based on the likeliness of their meaning. This survey discusses the existing similarity measures by partitioning them into two approaches: Corpus-based and Knowledge-based. The features, performance, advantages and disadvantages of various semantic similarity measures are discussed. The aim of this paper is to provide an efficient evaluation of all these measures and help the researchers to select the best measure according to their requirement.

Semantic similarity, Corpus-based similarity, Knowledge-based similarity, Semantic relatedness