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Showing 1 to 20 of 480 for “"Nlp"”.
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NLP City
… to understanding existing concepts and models in NLP by simplifying them into intuitive narratives of towns and cities. By leveraging this more familiar context, the hope is to provide more engagement and information retention to non-technical audience members. The complete narrative can be found …
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Exploiting knowledge in NLP
… for a large number of tasks. The first steps in NLP applications involve identification of topics, entities, concepts, and relations in text. Traditionally, statistical models have been successfully deployed for the aforementioned problems. However, the major trend so far has been: “scaling up by …
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Unsupervised Crypto Clustering with NLP
A cryptocurrency is a digital form of currency that is secured using an online ledger with cryptography. The first successful cryptocurrency was Bitcoin, which was launched in 2009 by an anonymous person under the pseudonym Satoshi Nakamoto. Similar to stocks, they can be bought and sold, and their …
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Neural Word Representations for Biomedical NLP
… the main input to Natural Language Processing (NLP)applications and in most areas of NLP, achieving cutting-edge results. Our work extends the usefulness of neural representations, with a particular emphasis on the biomedical domain which is linguistically highly challenging. We focus on three …
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NLP driven large scale financial data analysis
… source of data. Natural language preprocessing (NLP), as a classical yet still prosperous research domain, has seen astonishing progress with the development of deep learning and widely used for texts related tasks such as text sentiment analysis and recommendation system. However, currently …
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Identifying External Cross-references using Natural Language Processing (NLP)
… and novelty] We use Natural Language Processing (NLP), Pattern Recognition and Web Scrapping techniques for automatically extracting external cross-references from contractual requirements and prepare a map for representing related external cross-references to each contractual requirement. This …
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Challenges of computational social science analysis with NLP methods
… simpler sub-tasks. Then, we introduce NLP models with various configurations to automate two of the sub-tasks given by the requirement analysis, namely claim detection and classification, based on different neural network architectures ranging from unidirectional LSTMs to Transformer …
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NLP in Education: Enhancing Teacher Wellbeing and Professional Practice
… unstable systems. Neuro-Linguistic Programming (NLP) has a growing presence in practitioner-led coaching and wellbeing sectors internationally; however, its potential to support teacher sustainability in education remains under-examined and under-theorised. This qualitative study investigates how …
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Random Sequential Encoders for Private Data Release in NLP
There are many scenarios that motivate data owners to outsource the training of machine learning models on their data to external model developers. While doing so, it is of data owners’ best interests to keep their data private - meaning that no third party, including the model developer, can learn …
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Practical Considerations For the Deployment of Clinical NLP Systems
… (LLMs) have resulted in improvements on many NLP tasks, it remains unclear whether these models trained primarily with general web text are the right tool in highly specialized, safety critical domains such as healthcare. A healthcare system attempting to automate a clinical task must weigh …
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Controlling the effect of crowd noisy annotations in NLP Tasks
Natural Language Processing (NLP) is a sub-field of Artificial Intelligence and Linguistics, with the aim of studying problems in the automatic generation and understanding of natural language. It involves identifying and exploiting linguistic rules and variation with code to translate unstructured …
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Enhancing large language models: toward more reliable and equitable NLP
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms
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Pitfalls and possibilities: What NLP systems are missing out on
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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NLP measures for cyber environment safety: Detection, mitigation and intervention
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms
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Advancing NLP Frontiers in Information Extraction, Opinion Mining, and Text Synthesis
… AI and transformer architectures have propelled NLP toward systems capable of extracting, interpreting, and synthesizing information with greater accuracy and contextual awareness. This dissertation presents an integrated research program spanning three pillars: information extraction, opinion …
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Functional characterization of the novel centrosomal protein Nlp (ninein-like protein)
… a novel centrosomal component, the human protein Nlp (ninein-like protein) related to the previously characterized MT-anchoring protein ninein. In the first part of the present thesis we describe the identification of Nlp as a novel centrosomal substrate of Polo-like kinase 1 (Plk1), an important …
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Curtus: An NLP Tool to Map Job Skills to Academic Courses
<p>Many businesses are burdened with the need to train students for the job instead of finding them prepared for it. Few business leaders feel that colleges prepare students for future jobs from day one. It can be a challenge for colleges to determine if their curricula meet the industry needs. …
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An NLP Analysis of Health Advice Giving in the Medical Research Literature
… Compared to other natural language processing (NLP) applications, health advice has not been computationally modeled as a language construct either. A new information service for directly accessing health advice should be able to reduce information barriers and to provide external assessment in …
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Applications and Analysis of NLP Deep Learning Models for Antibiotic's Side Effects Classifications
<p>I introduce a novel recursive modification to the classical Goemans-Williamson MaxCut algorithm, offering improved performance in vectorized data clustering tasks. Focusing on the clustering of medical publications, I suggest to employ recursive iterations in conjunction with a dimension …
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