Similarity Based Information Retrieval Using Levenshtein Distance Algorithm

Abstract

Sentence similarity plays an important role in many text-related research and applications such as information retrieval, information recommendation, natural language processing, machine translation and translation memory, and etc. Calculating similarity between sentences is the basis of measuring the similarity between texts which is the key to document classification and clustering. Sentence similarity partially depends on the word similarity. This system will display a similar text of field, areas and other facts in document retrieval. This paper uses a sentence matching method of the Levenshtein Distance algorithm. The
similarity between words can be calculated from the spelling of words or the meaning of words. Sentence similarity: The similarities between words in different sentences have a great influence on the similarity between two sentences. This system is retrieved from a similar sentence that included Theories, Methods and other facts in the document database.