@inproceedings{9c509e4f57f24bdcaada99c3160bffed,
title = "Regression based approaches for detecting and measuring textual similarity",
abstract = "Finding Semantic similarity is an important component in various fields such as information retrieval, question-answering system, machine translation and text summarization. This paper describes two different approaches to find semantic similarity on SemEval 2016 dataset. First method is based on lexical analysis whereas second method is based on distributed semantic approach. Both approaches are trained using feed-forward neural network and layer-recurrent network to predict the similarity score.",
author = "Sandip Sarkar and Partha Pakray and Dipankar Das and Alexander Gelbukh",
note = "Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 4th International Conference on Mining Intelligence and Knowledge Exploration, MIKE 2016 ; Conference date: 13-11-2016 Through 19-11-2016",
year = "2017",
doi = "10.1007/978-3-319-58130-9_14",
language = "Ingl{\'e}s",
isbn = "9783319581293",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "144--152",
editor = "Rajendra Prasath and Alexander Gelbukh",
booktitle = "Mining Intelligence and Knowledge Exploration - 4th International Conference, MIKE 2016, Revised Selected Papers",
address = "Alemania",
}