The article is devoted to a review of approaches solving the problem identifying paraphrases. This problem's relevance and use in tasks such as plagiarism detection, text simplification, information search are described. Several classes solutions were considered. first approach based on manual rules - it uses manually selected features fundamental properties second lexical similarity various da...

The purpose behind Thavathiru Kundrakkudi Adigalar's paraphrase of Thirukkural is to spread the fame through world and enable people worldwide drink divine nectar Thirukkural. It also help practically apply essense day-to-day practical life without distorting its meaning. Adigalars simple as well clear covers politics, life, commerce, Vriddhashram, agriculture, day today style. this essay prese...

This paper proposes an approach to sentencelevel paraphrase identification by text canonicalization. The source sentence pairs are first converted into surface text that approximates canonical forms. A decision tree learning module which employs simple lexical matching features then takes the output canonicalized texts as its input for a supervised learning process. Experiments on the Microsoft...

We propose to re-examine the hypothesis that automated metrics developed for MT evaluation can prove useful for paraphrase identification in light of the significant work on the development of new MT metrics over the last 4 years. We show that a meta-classifier trained using nothing but recent MT metrics outperforms all previous paraphrase identification approaches on the Microsoft Research Par...

The task of paraphrase acquisition from related sentences can be tackled by a variety of techniques making use of various types of knowledge. In this work, we make the hypothesis that their performance can be increased if candidate paraphrases can be validated using information that characterizes paraphrases independently of the set of techniques that proposed them. We implement this as a bi-cl...

This study evaluates the robustness of established computational indices used to assess text relatedness in userlanguage. The original User-Language Paraphrase Corpus (ULPC) was compared to a corrected version, in which each paraphrase was corrected for typographical and grammatical errors. Error correction significantly affected values for each of five computational indices, indicating greater...

As research in text-to-text paraphrase generation progresses, it has the potential to improve the quality of generated text. However, the use of paraphrase generation methods creates a secondary problem. We must ensure that generated novel sentences are not inconsistent with the text from which it was generated. We propose a machine learning approach be used to filter out inconsistent novel sen...

Data sources like the clusters of news headlines at Google News present an exciting opportunity to learn paraphrase models from data automatically. We present both a novel dataset and a novel approach to automatic, unsupervised learning of paraphrase models from that datset. Leveraging existing NLP tools such as the Stanford Parser and lexical resources such as WordNet and Infomap, we construct...

Paraphrasing is an important aspect of language competence; however, EFL learners have long had difficulty paraphrasing in their writing owing to their limited language proficiency. Therefore, automatic paraphrase suggestion systems can be useful for writers. In this paper, we present PREFER 1 , a paraphrase reference tool for helping language learners improve their writing skills. In this pape...