Modeling sentence similarity is complicated by the ambiguity and variability of linguistic
expression. To cope with these challenges, we propose a model for comparing sentences …

Paraphrase detection is important for a number of applications, including plagiarism
detection, authorship attribution, question answering, text summarization, text mining in …

Paraphrase Generation is one of the most important and challenging tasks in the field of
Natural Language Generation. The paraphrasing techniques help to identify or to …

Representing discrete words in a continuous vector space turns out to be useful for natural
language applications related to text understanding. Meanwhile, it poses extensive …

In this paper, we propose a hybrid approach for sentence paraphrase identification. The
proposal addresses the problem of evaluating sentence-to-sentence semantic similarity …

This article presents our team's participating system at SemEval-2014 Task 3. Using a meta-
learning framework, we experiment with traditional knowledgebased metrics, as well as …

Semantic textual similarity methods are becoming increasingly crucial in text mining
research areas such as text retrieval and summarization. Existing methods of text similarity …

This paper presents the systems that we participated with in the Semantic Text Similarity task
at SEMEVAL 2012. Based on prior research in semantic similarity and relatedness, we …

Paraphrase detection (PD) is a very essential and important task in Natural language
processing. The goal of paraphrase detection is to check whether two statements written in …

This study is to examine paraphrase detection (PD) for diagnostic purposes. Which is
defined as the capability to find and discover the similarity between sentences that are …