natural language processing IEEE PAPERS-2020
Natural language processing involves the reading and understanding of spoken or written language through the medium of a computer. This includes, for example, the automatic translation of one language into another, but also spoken word recognition, or the automatic answering of questions
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing .
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Abstract We present GluonCV and GluonNLP, the deep learning toolkits for computer vision and natural language processing based on Apache MXNet (incubating). These toolkits provide state-of-the-art pre-trained models, training scripts, and training logs, to facilitate
Einsteins framework for natural language processing
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Natural Language Processing is the term used to describe methods and laws applied to language to understand it computationally. The existence of clear laws such as those in physics has never been considered the task, because perhaps-letters are not that visible as
Lorentz transformations and special relativity for natural language processing
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This paper aims at applying Lorentz transformations to Literal Variables (letters), introduced recently in the research titled: Einsteins framework for Natural Language Processing referred to bellow. We show that literal variables (when moving from local frame to another
Mathematical principles of natural language processing part i: Loop coordinates
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Letter [i] defines loops, the series of letters inside the first loop are:[t]. The series of letters inside the second loop are:[snotaboutbe]. The series of letters inside the third loop are:[ngs mart]. The series of letters inside the fourth loop are:[t]. The series of letters inside the fifth Purpose The highly structured nature of medical reports makes them feasible for automated large-scale patient identification. This study aimed to develop a natural language processing (NLP) model to retrospectively retrieve patients with presence and history of carotid stenosis
The coefficients of mind: The hidden secret of natural language processing
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Those coefficients are closely related to the structure of text under study, which is in turn related to the writers mind language package and the linguistic understanding associated with that package in that mind. Therefore, when writing several texts, that package (for
Introduction to Clinical Natural Language Processing with Python
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Background: Many of the most valuable insights in medicine are contained in written patient records. While some of these are coded into structured data as part of the record entry, many exist only as text. Although a complete understanding of this text is beyond current
From SARS to COVID-19: A bibliometric study on emerging infectious diseases with natural language processing technologies
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Abstract Background: On January 20 the novel coronavirus named COVID-19 aroused worldwide concern was identified by Chinese scientists. Many related research works were developed for the emerging, rapidly evolving situation of this epidemic. This
Deconstructing Persuasive Strategies in Mental Health Apps Based on User Reviews using Natural Language Processing
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Text Mining is concerned with extracting interesting and significant patterns or knowledge from unstructured text data. In this paper, we applied the text mining approach using natural language processing (NLP) techniques, especially topic modelling (with automated topic Purpose Natural language processing (NLP) can be used for automatic flagging of radiology reports. We assessed deep learning models for classifying non-English head CT reports. Methods We retrospectively collected head CT reports (2011 2018). Reports were signed in Basic elements of the law, such as statuses and regulations, are embodied in natural language and strictly depend on linguistic expressions. Hence, analyzing legal contents is a challenging task, and the legal domain is increasingly looking for automatic- processing
Proceedings of the Eighth International Workshop on Natural Language Processing for Social Media
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It is our great pleasure to welcome you to the Eighth Workshop on Natural Language Processing for Social Media-SocialNLP 201 associated with ACL 2020. SocialNLP is an inter-disciplinary area of natural language processing (NLP) and social computing. We hold
Ethical considerations of the GermEval20 Task 1. IQ assessment with natural language processing : Forbidden research or gain of knowledge
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Abstract The use of Intelligence Quotient (IQ) testing as a measure for intellectual ability is controversial. Even though IQ testing is considered to be among the most valid measures of psychology, findings and current research sparked a debate over racial or socioeconomicHigh dimensional data are rapidly growing in many different disciplines, particularly in natural language processing . The analysis of natural language processing requires working with high dimensional matrices of word embeddings obtained from text data. Those matrices The aim of this study is to develop an automated classification method for Brain Tumor Reporting and Data System (BT-RADS) categories from unstructured and structured brain magnetic resonance imaging (MR) reports. This retrospective study included 1410 BT-RADS Length of stay (LOS) and discharge destination predictions are key parts of the discharge planning process for general medical hospital inpatients. It is possible that machine learning, using natural language processing be able to assist with accurate LOS and
A Hybrid Reporting Platform for Extended RadLex Coding Combining Structured Reporting Templates and Natural Language Processing
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Structured reporting is a favorable and sustainable form of reporting in radiology. Among its advantages are better presentation, clearer nomenclature, and higher quality. By using MRRT-compliant templates, the content of the categorized items (eg, select fields) can be
Introductory Tutorial: Commonsense Reasoning for Natural Language Processing
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Commonsense knowledge, such as knowing that bumping into people annoys them or rain makes the road slippery , helps humans navigate everyday situations seamlessly (Apperly). Yet, endowing machines with such human-like commonsense reasoning
Language Translation Using Natural Language Processing
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Natural language processing (NLP) has recently gained much attention for representing and analyzing human language computationally. Its spread its applications in various fields like artificial intelligence, email spam detection, information extraction, summarization, medical
A Survey on Natural Language Processing in context with Machine Learning
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Natural Language Processing study has reached a point where distinct machine learning algorithms were implemented in order to obtain better results in the classification of text. This paper presents many previous research works in this field of interest. It discusses the
Towards Efficient and Reproducible Natural Language Processing
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Machine learning has reported remarkable progress on a broad range of tasks, including machine translation, object recognition, and game playing (Shoham et al.). Much of this progress has been achieved by increasingly large and computationally-intensive deep
Natural language processing : machine learning and modelling linguistics in the domain of sentiment analysis
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1.1 Background Andrew Ng, a leading figure in the field of artificial intelligence, has long predicted that as speech recognition goes from 95% accurate to 99% accurate, it will become the primary way that we interact with computers (Jain, Kulkarni, and Shah)Purpose Due to the exceptionally high standards for accuracy and data integrity in scientific regulatory reporting, it is vital that any tool that aims to streamline this process is as efficient or more in gathering data as a team of scientists, without higher cost in terms of time orIntroduction Atopic dermatitis (AD) is an incurable, inflammatory skin disease characterized by skin barrier disruption and immune dysregulation. Although AD is considered a childhood disease, adult onset is possible, presenting with daily sleep disturbance and functional
DATA-DRIVEN PRODUCT DEVELOPMENT: PATENT DATA ANALYSIS USING NATURAL LANGUAGE PROCESSING
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R Saab scholarworks.aub.edu.lb The product development lifecycle exhibits many big data flows of internal or external sources and destinations. Until recently, means of analyzing these data flows were severely limited due to performance and storage limits. With the advancement in technology, one can
GRAPH NEURAL NET APPLICATIONS FOR NATURAL LANGUAGE PROCESSING
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Graphs are widely used in natural language processing (NLP) research from the era of expert systems, such as WordNet (Fellbaum 1998), a graph-based representations of words meanings through their relations with other words (Quillian 1968). Graph-based
Proactive Natural Language Processing : Addressing Terminology Disparity and Team Coalescence
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There is a continuing need for battlefield simulations and virtual humans. Most recently, the authors have been focused on the creation of virtual conversation environments to leverage the mentoring skills of selected individuals by creating large libraries of short video clips of
CYBER BULLYING IDENTIFICATION AND TACKLING USING NATURAL LANGUAGE PROCESSING TECHNIQUES
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As offensive content has a detrimental influence on the internet and especially in social media, there has been much research identifying cyberbullying posts from social media datasets. Previous works on this topic have overlooked the problems for cyberbullying
A content comparison analysis between traditional Chinese medicine and Hui medicine using natural language processing and bootstrapping methods
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Objective: The purpose of this work was to estimate the similarity in content between traditional using natural language processing technique and bootstrapping methods. Methods: Qualitative analyses were conducted to extract the knowledge frameworks of
A Study on Natural Language Processing approaches for Text2Image using Machine Learning Algorithms
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Abstract Now a days, Natural Language Processing (NLP) tasks are everywhere around us like, suggest in search, automatic Gmail replies, machine translation. The challenges in the field of NLP, is having lots of text data in the form of reviews available in the online platformsA Language is a means of communication among humans. It has a structure and is defined by the rules of grammar, which govern the constitution of sentences, clauses and words. Linguistics, the scientific study of language concerns itself with a wide variety of topics such
Natural language processing : A literature survey
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It is quite hard to imagine a smart system like a voice assistant or a chat-bot or a recommender system without Natural Language Processing (NLP). It all starts with an initial unit that first interprets the data (audio or text) provided and then start making sense of the
The Influence of Structural Information on Natural Language Processing
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Learning effective and efficient vectoral representations for text has been a core problem for many downstream tasks in natural language processing (NLP). Most traditional NLP approaches learn a text representation by only modeling the text itself. Recently
Evaluating Weight Agnostic Neural Networks on Natural Language Processing Tasks
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Abstract Weight Agnostic Neural Networks (Gaier and Ha) describes a method of searching for neural network architectures that perform much better than chance on image classification and reinforcement learning tasks despite having random weights. In this work
The Survey: Advances in Natural Language Processing using Deep Learning
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Natural Language Processing using Deep Learning is one of the critical areas of Artificial Intelligence to focus in the next decades. Over the last few years, Artificial intelligence had evolved by maturing critical areas in research and development. The latest developments in
Fast neural network engine for natural science language processing : a drug-search case.
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The main advantage of modern natural language processing methods is a possibility to turn an amorphous human-readable task into a strict mathematic form. That allows to extract chemical data and insights from articles and to find new semantic relations. We propose a
A Study of Transfer Learning Methods within Natural Language Processing and Reinforcement Learning
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The classic supervised machine learning paradigm is based on learning in isolation, where each task is solved by using a separate model with a single dataset. Transfer learning is a set of methods used to overcome the isolated learning paradigm by utilizing knowledge
NATURAL LANGUAGE PROCESSING : PERFORMANCE APPROACHES AND UP-TO-DATE TASKS
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SCIENCE, RESEARCH, DEVELOPMENT ¦28 used during the program implementation of the above steps. Scientists propose more sophisticated methods of word separation in a sentence, and great attention is given to the separation of word collocation to correctly
Techniques Comparison for Natural Language Processing
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These improvements open many possibilities in solving Natural Language Processing downstream tasks. Such tasks include machine translation, speech recognition, information retrieval, sentiment analysis, summarization, question answering, multilingual dialogue
Machine Learning Applied in Natural Language Processing
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Abstract Machine Learning is present in our lives now more than ever. One of the most researched areas in machine learning is focused on creating systems that are able to understand natural language . Natural language processing is a broad domain, having a
Ten Ways of Leveraging Ontologies for Rapid Natural Language Processing Customization for Multiple Use Cases in Disjoint Domains
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With the ever-growing adoption of AI technologies by large enterprises, purely data-driven approaches have dominated the field in the recent years. For a single use case, a development process looks simple: agreeing on an annotation schema, labeling the data
Leveraging AI for Psychiatric Research: Natural Language Processing to Assess Loneliness in Older Adults
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Artificial intelligence (AI) and machine learning (ML) are a promising and disruptive new approach to healthcare, though its application in mental health research and clinical care has lagged behind fields like radiology. Natural language processing (NLP) has great
Sentiment Analysis using Natural Language Processing
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Nowadays text synthesis is most vital part of web technology. NLP are often a subfield of linguistics, computing, information engineering, and AI concerned with the interactions between computers and human ( natural ) languages, especially the way to program
Natural Language Processing : How do humans process language
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Language processing is basically an inverse problem: Colorless green ideas sleep furiously The Sally hugged him the Thomas Time flies like an arrow The apartment that the maid who the service had sent over was decorated Keine Kopfverletzung ist zu harmlos um sie nicht
3rd workshop on natural language processing for requirements engineering (NLP4RE20)
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Natural language processing (NLP) plays an important role in several areas of software engineering, and requirements engineering (RE) is not an exception. Requirements are generally authored and communicated in textual form and in different levels of formality, from
REINSTATING AND ACHIEVING AGILE THROUGH NATURAL LANGUAGE PROCESSING
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Its an Agile mania that is revolutionizing the software industry. The common meaning of Agile is to move quickly and easily. Using Agile methodology work is done in an easy and convenient way and projects are delivered in a serialized process rather than delivering it atData Delicacy is one of the most important issue now a days, not only storing it requires a lot of storage space but even kills a lot of time. These generally happens in online discussion forums mostly, Quora is one of them. This paper gives an insight into handling the problem
Proceedings of the 2nd Workshop on Natural Language Processing for Conversational AI
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Ever since the invention of the intelligent machine, hundreds and thousands of mathematicians, linguists, and computer scientists have dedicated their career to empowering human-machine communication in natural language . Although the idea is
From Smartphone Zombies to Natural Language Processing Designing and Evaluating Behavior Change Support Systems
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The Eighth International Workshop on Behavior Change Support Systems was held as a virtual event due to the CoVid19 crisis. Despite of the challenging situation, researchers from around the globe joined together to discuss recent advances in Behavior Change Support
Natural Language Processing for Information and Project Management
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The purpose of the paper is to investigate the state of the art of textual translation theories, methods, and tools into formal and numerical requirements to support information modelling and project management process. Natural Language Processing helps translate text
Industrial Accident Report Analysis Using Natural Language Processing
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Industrial safety stays basic worry in many nations. Industrial accidents cause human suffering as well as result in immense money related misfortune and ecological effects. To counteract these accidents in the future, the examination of the risk control plan is basic. In
Understanding 21st Century Bordeaux Wines from Wine Reviews Through Natural Language Processing and Classifications
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Wine has been popular with the public for centuries; in the market, there are a variety of wines to choose from. Among all, Bordeaux, France, is considered as the most famous wine region in the world. In this research, we try to understand Bordeaux wines made in the 21st
Reducing Gender Bias in Natural Language Processing methods
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As in most fields today, gender bias is a problem in research and threatens the expected neutrality of research outputs. In this study we explored possible suitable methods for limiting gender bias in the research field of Natural Language Processing (NLP) by
Data collection for natural language processing systems
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Any NLP system needs enough data for training and testing purposes. They can be split into two datasets: correct and incorrect (erroneous) data. Usually, it is not a problem to find and get a set of correct data because the correct texts are available from different sources Plagiarism detection is gaining importance due to requirements for integrity in Research works especially when it comes to Cross-lingual plagiarism. In this paper, we have researched a new approach for Cross-Lingual sentence level plagiarism detection. The
A Gentle Introduction to Deep Learning for Natural Language Processing
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An obvious question that pop up when seeing this material is: Why another deep learning and natural language processing book Several excellent ones have been published, covering both theoretical and practical aspects of deep learning and its
Integrated Natural Language Processing and Meta-Network Analysis for Social Sensing of Location-Event-Actor Nexus in Disasters
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The objective of this study is to propose and test a methodological framework that integrates natural language processing and meta-network analysis to leverage social media data for situation assessment and action prioritization in disasters. Situation assessment based on
Knowledge Bases And Statistical Natural Language Processing
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In early years of artificial intelligence, researchers were trying to emulate the decision- making ability of a human expert which is termed as expert systems. An expert system is normally consist of two main subsystems: Knowledge Base (KB) and Reasoning Engine
Natural Language Processing Coursework
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In this project, we are tasked with creating a regression model to predict the quality of a machine-translated sentence. While trying multiple Pre- processing steps, word representations techniques and different neural network architectures we discovered that
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