Proceedings ArticleDOI
Machine Learning Models for Paraphrase Identification and its Applications on Plagiarism Detection
Ethan Hunt,Binay Dahal,Justin Zhan,Laxmi Gewali,Paul Oh,Ritvik Janamsetty,Chanana Kinares,Chanel Koh,Alexis Sanchez,Felix Zhan,Murat Ozdemir,Shabnam Waseem,Osman Yolcu +12 more
- pp 97-104
TLDR
Among the compared models, as expected, Recurrent Neural Network is best suited for the paraphrase identification task and it is proposed that Plagiarism detection is one of the areas where Paraphrase Identification can be effectively implemented.Abstract:
Paraphrase Identification or Natural Language Sentence Matching (NLSM) is one of the important and challenging tasks in Natural Language Processing where the task is to identify if a sentence is a paraphrase of another sentence in a given pair of sentences. Paraphrase of a sentence conveys the same meaning but its structure and the sequence of words varies. It is a challenging task as it is difficult to infer the proper context about a sentence given its short length. Also, coming up with similarity metrics for the inferred context of a pair of sentences is not straightforward as well. Whereas, its applications are numerous. This work explores various machine learning algorithms to model the task and also applies different input encoding scheme. Specifically, we created the models using Logistic Regression, Support Vector Machines, and different architectures of Neural Networks. Among the compared models, as expected, Recurrent Neural Network (RNN) is best suited for our paraphrase identification task. Also, we propose that Plagiarism detection is one of the areas where Paraphrase Identification can be effectively implemented.read more
Citations
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Journal ArticleDOI
Deep Physical Informed Neural Networks for Metamaterial Design
Zhiwei Fang,Justin Zhan +1 more
TL;DR: A physical informed neural network approach for designing the electromagnetic metamaterial and a method to solve high frequency Helmholtz equation, which is widely used in physics and engineering is proposed.
Journal ArticleDOI
BLSTM-API: Bi-LSTM Recurrent Neural Network-Based Approach for Arabic Paraphrase Identification
TL;DR: In this paper, an Arabic extrinsic paraphrase identification method is proposed based on a Siamese recurrent neural networks architecture, which is useful for identifying semantic similarity between the obtained source and suspect vectors.
Journal ArticleDOI
An Evolutionary Approach to Compact DAG Neural Network Optimization
Carter Chiu,Justin Zhan +1 more
TL;DR: This work proposes the use of compact directed acyclic graph neural networks (DAG-NNs) and an evolutionary approach for automating the optimization of their structure and parameters and demonstrates that this approach consistently outperforms conventional neural networks, even while employing fewer nodes.
Proceedings ArticleDOI
A Study of Ensemble Methods for Cyber Security
Nicholas Lower,Felix Zhan +1 more
TL;DR: This study looks at the advantages of ensemble methods when applied to the cybersecurity domain by using the widely used NSL-KDD intrusion detection dataset, specifically the algorithms experimented with are the Voting classifier, boosting, Random forest classifier and AdaBoost classifier.
Proceedings ArticleDOI
Segregating Hazardous Waste Using Deep Neural Networks in Real-Time Video
TL;DR: Through the use of machine learning, the model is able to identify hazardous objects and recyclable items within a pile of trash to help protect all individuals.
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Posted Content
Neural Machine Translation by Jointly Learning to Align and Translate
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Proceedings ArticleDOI
SQuAD: 100,000+ Questions for Machine Comprehension of Text
TL;DR: The Stanford Question Answering Dataset (SQuAD) as mentioned in this paper is a reading comprehension dataset consisting of 100,000+ questions posed by crowdworkers on a set of Wikipedia articles, where the answer to each question is a segment of text from the corresponding reading passage.
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