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Thematische Bibliographien / Clinical Natural Language Processing / Dissertationen

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Dissertationen zum Thema „Clinical Natural Language Processing“

Autor: Grafiati

Veröffentlicht am 25. Mai 2024

Zuletzt aktualisiert am 31. Juli 2025

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1

Chien, Isabel. "Natural language processing for precision clinical diagnostics and treatment." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119754.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 61-65).<br>In this thesis, I focus upon application of natural language processing to clinical diagnostics and treatment within the palliative care and serious illness field. I explore a variety of natural language processin

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Mehrabi, Saeed. "Advanced natural language processing and temporal mining for clinical discovery." Thesis, Indiana University - Purdue University Indianapolis, 2016. http://pqdtopen.proquest.com/#viewpdf?dispub=10032405.

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<p> There has been vast and growing amount of healthcare data especially with the rapid adoption of electronic health records (EHRs) as a result of the HITECH act of 2009. It is estimated that around 80% of the clinical information resides in the unstructured narrative of an EHR. Recently, natural language processing (NLP) techniques have offered opportunities to extract information from unstructured clinical texts needed for various clinical applications. A popular method for enabling secondary uses of EHRs is information or concept extraction, a subtask of NLP that seeks to locate and classi

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Forsyth, Alexander William. "Improving clinical decision making with natural language processing and machine learning." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112847.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 49-53).<br>This thesis focused on two tasks of applying natural language processing (NLP) and machine learning to electronic health records (EHRs) to improve clinical decision making. The first task was to predict cardiac re

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Regulapati, Sushmitha. "Natural language processing framework to assist in the evaluation of adherence to clinical guidelines." Morgantown, W. Va. : [West Virginia University Libraries], 2007. https://eidr.wvu.edu/etd/documentdata.eTD?documentid=5340.

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Thesis (M.S.)--West Virginia University, 2007.<br>Title from document title page. Document formatted into pages; contains vii, 36 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 33-36).

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Leonhard, Annette Christa. "Automated question answering for clinical comparison questions." Thesis, University of Edinburgh, 2012. http://hdl.handle.net/1842/6266.

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This thesis describes the development and evaluation of new automated Question Answering (QA) methods tailored to clinical comparison questions that give clinicians a rank-ordered list of MEDLINE® abstracts targeted to natural language clinical drug comparison questions (e.g. ”Have any studies directly compared the effects of Pioglitazone and Rosiglitazone on the liver?”). Three corpora were created to develop and evaluate a new QA system for clinical comparison questions called RetroRank. RetroRank takes the clinician’s plain text question as input, processes it and outputs a rank-ordered lis

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Eglowski, Skylar. "CREATE: Clinical Record Analysis Technology Ensemble." DigitalCommons@CalPoly, 2017. https://digitalcommons.calpoly.edu/theses/1771.

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In this thesis, we describe an approach that won a psychiatric symptom severity prediction challenge. The challenge was to correctly predict the severity of psychiatric symptoms on a 4-point scale. Our winning submission uses a novel stacked machine learning architecture in which (i) a base data ingestion/cleaning step was followed by the (ii) derivation of a base set of features defined using text analytics, after which (iii) association rule learning was used in a novel way to generate new features, followed by a (iv) feature selection step to eliminate irrelevant features, followed by a (v)

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Wang, Yefeng. "Information extraction from clinical notes." Thesis, The University of Sydney, 2010. https://hdl.handle.net/2123/28844.

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Information Extraction (IE) is an important task for Natural Language Processing (NLP). Effective IE methods, aimed at constructing structured information for unstructured natural language text, can reduce a large amount of human effort in processing the digital information available today. Successful application of IE to the clinical domain can advance clinical research and provide underlying techniques to support better health information systems. This thesis investigates the problems of IE from clinical notes.

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Henriksson, Aron. "Semantic Spaces of Clinical Text : Leveraging Distributional Semantics for Natural Language Processing of Electronic Health Records." Licentiate thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-94344.

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The large amounts of clinical data generated by electronic health record systems are an underutilized resource, which, if tapped, has enormous potential to improve health care. Since the majority of this data is in the form of unstructured text, which is challenging to analyze computationally, there is a need for sophisticated clinical language processing methods. Unsupervised methods that exploit statistical properties of the data are particularly valuable due to the limited availability of annotated corpora in the clinical domain. Information extraction and natural language processing system

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Khizra, Shufa. "Using Natural Language Processing and Machine Learning for Analyzing Clinical Notes in Sickle Cell Disease Patients." Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright154759374321405.

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Islam, Mohammed Ashrafull. "Enhancing the interactivity of a clinical decision support system by using knowledge engineering and natural language processing." Thesis, Aston University, 2018. http://publications.aston.ac.uk/37540/.

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Mental illness is a serious health problem and it affects many people. Increasingly,Clinical Decision Support Systems (CDSS) are being used for diagnosis and it is important to improve the reliability and performance of these systems. Missing a potential clue or a wrong diagnosis can have a detrimental effect on the patient's quality of life and could lead to a fatal outcome. The context of this research is the Galatean Risk and Safety Tool (GRiST), a mental-health-risk assessment system. Previous research has shown that success of a CDSS depends on its ease of use, reliability and interactivi

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Alnazzawi, Noha Abdulkareem D. "Linking clinical records to the biomedical literature." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/linking-clinical-records-to-the-biomedical-literature(7ab62b2f-2178-49f3-9b5f-a8c15598cae7).html.

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Narrative information in Electronic Health Records (EHRs) contains a wealth of clinical information about treatments, diagnosis, medication and family history. In addition, the scientific literature represents a rich source of information that summarises the latest results and new research findings relevant to different diseases. These two textual sources often contain different types of valuable phenotypic information that may be complementary to each other. Combining details from each source thus has the potential to be useful in uncovering new disease-phenotypic associations. In turn, these

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Gaschi, Félix. "Understanding and Evaluating Unsupervised Cross-lingual Embeddings in the General and in the Clinical Domains." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0347.

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Les données labellisées et non labellisées sont plus souvent disponibles en anglais que dans d'autres langues. Dans le domaine clinique, les données non anglaises peuvent être encore plus rares. Les représentations, ou plongements lexicaux, multilingues peuvent avoir deux propriétés utiles dans cette situation. La première est l'alignement multilingue, où les représentations de différentes langues partagent le même espace latent. Plus concrètement, les mots qui sont la traduction l'un de l'autre doivent avoir des représentations similaires. La deuxième propriété est l'apprentissage par transfe

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Dehghan, Azad. "Mining patient journeys from healthcare narratives." Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/mining-patient-journeys-from-healthcare-narratives(69ebfa6d-764a-4dfe-bbf8-6aab1905a6f3).html.

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The aim of the thesis is to investigate the feasibility of using text mining methods to reconstruct patient journeys from unstructured clinical narratives. A novel method to extract and represent patient journeys is proposed and evaluated in this thesis. A composition of methods were designed, developed and evaluated to this end; which included health-related concept extraction, temporal information extraction, and concept clustering and automated work-flow generation. A suite of methods to extract clinical information from healthcare narratives were proposed and evaluated in order to enable c

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Shivade, Chaitanya P. "How sick are you?Methods for extracting textual evidence to expedite clinical trial screening." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1462810822.

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Tang, Huaxiu. "Detecting Adverse Drug Reactions in Electronic Health Records by using the Food and Drug Administration’s Adverse Event Reporting System." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1470753258.

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Velupillai, Sumithra. "Shades of Certainty : Annotation and Classification of Swedish Medical Records." Doctoral thesis, Stockholms universitet, Institutionen för data- och systemvetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-74828.

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Access to information is fundamental in health care. This thesis presents research on Swedish medical records with the overall goal of building intelligent information access tools that can aid health personnel, researchers and other professions in their daily work, and, ultimately, improve health care in general. The issue of ethics and identifiable information is addressed by creating an annotated gold standard corpus and porting an existing de-identification system to Swedish from English. The aim is to move towards making textual resources available to researchers without risking exposure

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Bustos, Aurelia. "Extraction of medical knowledge from clinical reports and chest x-rays using machine learning techniques." Doctoral thesis, Universidad de Alicante, 2019. http://hdl.handle.net/10045/102193.

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This thesis addresses the extraction of medical knowledge from clinical text using deep learning techniques. In particular, the proposed methods focus on cancer clinical trial protocols and chest x-rays reports. The main results are a proof of concept of the capability of machine learning methods to discern which are regarded as inclusion or exclusion criteria in short free-text clinical notes, and a large scale chest x-ray image dataset labeled with radiological findings, diagnoses and anatomic locations. Clinical trials provide the evidence needed to determine the safety and effectiveness o

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Kempf, Emmanuelle. "Structuration, standardisation et enrichissement par traitement automatique du langage des données relatives au cancer au sein de l’entrepôt de données de santé de l’Assistance Publique – Hôpitaux de Paris." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS694.

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Le cancer est un enjeu de santé publique dont l’amélioration de la prise en charge repose, entre autres leviers, sur l’exploitation d’entrepôts de données de santé (EDS). Leur utilisation implique la maîtrise d’obstacles tels que la qualité, la standardisation et la structuration des données de soins qui y sont stockées. L’objectif de cette thèse était de démontrer qu’il est possible de lever les verrous d’utilisation secondaire des données de l’EDS de l’Assistance Publique - Hôpitaux de Paris (AP-HP) concernant des patients atteints de cancer à diverses finalités telles que le pilotage de la

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Matsubara, Shigeki. "Corpus-based Natural Language Processing." INTELLIGENT MEDIA INTEGRATION NAGOYA UNIVERSITY / COE, 2004. http://hdl.handle.net/2237/10355.

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Smith, Sydney. "Approaches to Natural Language Processing." Scholarship @ Claremont, 2018. http://scholarship.claremont.edu/cmc_theses/1817.

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This paper explores topic modeling through the example text of Alice in Wonderland. It explores both singular value decomposition as well as non-‐‑negative matrix factorization as methods for feature extraction. The paper goes on to explore methods for partially supervised implementation of topic modeling through introducing themes. A large portion of the paper also focuses on implementation of these techniques in python as well as visualizations of the results which use a combination of python, html and java script along with the d3 framework. The paper concludes by presenting a mixture of S

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Strandberg, Aron, and Patrik Karlström. "Processing Natural Language for the Spotify API : Are sophisticated natural language processing algorithms necessary when processing language in a limited scope?" Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-186867.

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Knowing whether you can implement something complex in a simple way in your application is always of interest. A natural language interface is some- thing that could theoretically be implemented in a lot of applications but the complexity of most natural language processing algorithms is a limiting factor. The problem explored in this paper is whether a simpler algorithm that doesn’t make use of convoluted statistical models and machine learning can be good enough. We implemented two algorithms, one utilizing Spotify’s own search and one with a more accurate, o✏ine search. With the best precis

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Chen, Joseph C. H. "Quantum computation and natural language processing." [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=965581020.

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Knight, Sylvia Frances. "Natural language processing for aerospace documentation." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621395.

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Naphtal, Rachael (Rachael M. ). "Natural language processing based nutritional application." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/100640.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2015.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 67-68).<br>The ability to accurately and eciently track nutritional intake is a powerful tool in combating obesity and other food related diseases. Currently, many methods used for this task are time consuming or easily aban

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Eriksson, Simon. "COMPARING NATURAL LANGUAGE PROCESSING TO STRUCTURED QUERY LANGUAGE ALGORITHMS." Thesis, Umeå universitet, Institutionen för datavetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-163310.

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Using natural language processing to create Structured Query Language (SQL) queries has many benefits in theory. Even though SQL is an expressive and powerful language it requires certain technical knowledge to use. An interface effectively utilizing natural language processing would instead allow the user to communicate with the SQL database as if they were communicating with another human being. In this paper I compare how two of the currently most advanced open source algorithms (TypeSQL and SyntaxSQL) in this field can understandadvanced SQL. I show that SyntaxSQL is signicantly more ac

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Kesarwani, Vaibhav. "Automatic Poetry Classification Using Natural Language Processing." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37309.

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Poetry, as a special form of literature, is crucial for computational linguistics. It has a high density of emotions, figures of speech, vividness, creativity, and ambiguity. Poetry poses a much greater challenge for the application of Natural Language Processing algorithms than any other literary genre. Our system establishes a computational model that classifies poems based on similarity features like rhyme, diction, and metaphor. For rhyme analysis, we investigate the methods used to classify poems based on rhyme patterns. First, the overview of different types of rhymes is given along

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Pham, Son Bao Computer Science &amp Engineering Faculty of Engineering UNSW. "Incremental knowledge acquisition for natural language processing." Awarded by:University of New South Wales. School of Computer Science and Engineering, 2006. http://handle.unsw.edu.au/1959.4/26299.

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Linguistic patterns have been used widely in shallow methods to develop numerous NLP applications. Approaches for acquiring linguistic patterns can be broadly categorised into three groups: supervised learning, unsupervised learning and manual methods. In supervised learning approaches, a large annotated training corpus is required for the learning algorithms to achieve decent results. However, annotated corpora are expensive to obtain and usually available only for established tasks. Unsupervised learning approaches usually start with a few seed examples and gather some statistics based on a

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張少能 and Siu-nang Bruce Cheung. "A concise framework of natural language processing." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1989. http://hub.hku.hk/bib/B31208563.

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Cahill, Lynne Julie. "Syllable-based morphology for natural language processing." Thesis, University of Sussex, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386529.

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This thesis addresses the problem of accounting for morphological alternation within Natural Language Processing. It proposes an approach to morphology which is based on phonological concepts, in particular the syllable, in contrast to morpheme-based approaches which have standardly been used by both NLP and linguistics. It is argued that morpheme-based approaches, within both linguistics and NLP, grew out of the apparently purely affixational morphology of European languages, and especially English, but are less appropriate for non-affixational languages such as Arabic. Indeed, it is claimed

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Lei, Tao Ph D. Massachusetts Institute of Technology. "Interpretable neural models for natural language processing." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/108990.

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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 109-119).<br>The success of neural network models often comes at a cost of interpretability. This thesis addresses the problem by providing justifications behind the model's structure and predictions. In the first part of this thesis, we present a class of sequence operations for text processing. The proposed component generalizes from convolution operations and gated aggregations. As justi

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Grinman, Alex J. "Natural language processing on encrypted patient data." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/113438.

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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 85-86).<br>While many industries can benefit from machine learning techniques for data analysis, they often do not have the technical expertise nor computational power to do so. Therefore, many organizations would benefit fr

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Alharthi, Haifa. "Natural Language Processing for Book Recommender Systems." Thesis, Université d'Ottawa / University of Ottawa, 2019. http://hdl.handle.net/10393/39134.

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The act of reading has benefits for individuals and societies, yet studies show that reading declines, especially among the young. Recommender systems (RSs) can help stop such decline. There is a lot of research regarding literary books using natural language processing (NLP) methods, but the analysis of textual book content to improve recommendations is relatively rare. We propose content-based recommender systems that extract elements learned from book texts to predict readers’ future interests. One factor that influences reading preferences is writing style; we propose a system that recomme

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Medlock, Benjamin William. "Investigating classification for natural language processing tasks." Thesis, University of Cambridge, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.611949.

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Huang, Yin Jou. "Event Centric Approaches in Natural Language Processing." Doctoral thesis, Kyoto University, 2021. http://hdl.handle.net/2433/265210.

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Woldemariam, Yonas Demeke. "Natural language processing in cross-media analysis." Licentiate thesis, Umeå universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-147640.

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A cross-media analysis framework is an integrated multi-modal platform where a media resource containing different types of data such as text, images, audio and video is analyzed with metadata extractors, working jointly to contextualize the media resource. It generally provides cross-media analysis and automatic annotation, metadata publication and storage, searches and recommendation services. For on-line content providers, such services allow them to semantically enhance a media resource with the extracted metadata representing the hidden meanings and make it more efficiently searchable. Wi

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Cheung, Siu-nang Bruce. "A concise framework of natural language processing /." [Hong Kong : University of Hong Kong], 1989. http://sunzi.lib.hku.hk/hkuto/record.jsp?B12432544.

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Dawborn, Timothy James. "DOCREP: Document Representation for Natural Language Processing." Thesis, The University of Sydney, 2015. http://hdl.handle.net/2123/14767.

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The field of natural language processing (NLP) revolves around the computational interpretation and generation of natural language. The language typically processed in NLP occurs in paragraphs or documents rather than in single isolated sentences. Despite this, most NLP tools operate over one sentence at a time, not utilising the context outside of the sentence nor any of the metadata associated with the underlying document. One pragmatic reason for this disparity is that representing documents and their annotations through an NLP pipeline is difficult with existing infrastructure. Representin

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Miao, Yishu. "Deep generative models for natural language processing." Thesis, University of Oxford, 2017. http://ora.ox.ac.uk/objects/uuid:e4e1f1f9-e507-4754-a0ab-0246f1e1e258.

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Deep generative models are essential to Natural Language Processing (NLP) due to their outstanding ability to use unlabelled data, to incorporate abundant linguistic features, and to learn interpretable dependencies among data. As the structure becomes deeper and more complex, having an effective and efficient inference method becomes increasingly important. In this thesis, neural variational inference is applied to carry out inference for deep generative models. While traditional variational methods derive an analytic approximation for the intractable distributions over latent variables, here

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Hu, Jin. "Explainable Deep Learning for Natural Language Processing." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254886.

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Deep learning methods get impressive performance in many Natural Neural Processing (NLP) tasks, but it is still difficult to know what happened inside a deep neural network. In this thesis, a general overview of Explainable AI and how explainable deep learning methods applied for NLP tasks is given. Then the Bi-directional LSTM and CRF (BiLSTM-CRF) model for Named Entity Recognition (NER) task is introduced, as well as the approach to make this model explainable. The approach to visualize the importance of neurons in Bi-LSTM layer of the model for NER by Layer-wise Relevance Propagation (LRP)

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Gainon, de Forsan de Gabriac Clara. "Deep Natural Language Processing for User Representation." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS274.

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La dernière décennie a vu s’imposer le développement des méthodes de Deep Learning (DL), aussi bien dans le monde académique qu’industriel. Ce succès peut s’expliquer par la capacité du DL à modéliser des entités toujours plus complexes. En particulier, les méthodes de Representation Learning se concentrent sur l’apprentissage de représentations latentes issues de données hétérogènes, à la fois versatiles et réutilisables, notamment en Natural Language Processing (NLP). En parallèle, le nombre grandissant de systèmes reposant sur des données utilisateurs entraînent leur lot de défis.Cette thès

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Guy, Alison. "Logical expressions in natural language conditionals." Thesis, University of Sunderland, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.278644.

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Bannour, Nesrine. "Information Extraction from Electronic Health Records : Studies on temporal ordering, privacy and environmental impact." Electronic Thesis or Diss., université Paris-Saclay, 2023. http://www.theses.fr/2023UPASG082.

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L'extraction automatique des informations contenues dans les Dossiers Patients Informatisés (DPIs) est cruciale pour améliorer la recherche clinique. Or, la plupart des informations sont sous forme de texte non structuré. La complexité et le caractère confidentiel du texte clinique présente des défis supplémentaires. Par conséquent, le partage de données est difficile dans la pratique et est strictement encadré par des réglementations. Les modèles neuronaux offrent de bons résultats pour l'extraction d'informations. Mais ils nécessitent de grandes quantités de données annotées, qui sont souven

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Walker, Alden. "Natural language interaction with robots." Diss., Connect to the thesis, 2007. http://hdl.handle.net/10066/1275.

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Fuchs, Gil Emanuel. "Practical natural language processing question answering using graphs /." Diss., Digital Dissertations Database. Restricted to UC campuses, 2004. http://uclibs.org/PID/11984.

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Kolak, Okan. "Rapid resource transfer for multilingual natural language processing." College Park, Md. : University of Maryland, 2005. http://hdl.handle.net/1903/3182.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2005.<br>Thesis research directed by: Dept. of Linguistics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Takeda, Koichi. "Building Natural Language Processing Applications Using Descriptive Models." 京都大学 (Kyoto University), 2010. http://hdl.handle.net/2433/120372.

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Åkerud, Daniel, and Henrik Rendlo. "Natural Language Processing from a Software Engineering Perspective." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-2056.

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This thesis is intended to deal with questions related to the processing of naturally occurring texts, also known as natural language processing (NLP). The subject will be approached from a software engineering perspective, and the problem description will be formulated thereafter. The thesis is roughly divided into two major parts. The first part contains a literature study covering fundamental concepts and algorithms. We discuss both serial and parallel architectures, and conclude that different scenarios call for different architectures. The second part is an empirical evaluation of an NLP

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Byström, Adam. "From Intent to Code : Using Natural Language Processing." Thesis, Uppsala universitet, Avdelningen för datalogi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325238.

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Programming and the possibility to express one’s intent to a machine is becoming a very important skill in our digitalizing society. Today, instructing a machine, such as a computer to perform actions is done through programming. What if this could be done with human language? This thesis examines how new technologies and methods in the form of Natural Language Processing can be used to make programming more accessible by translating intent expressed in natural language into code that a computer can execute. Related research has studied using natural language as a programming language and usin

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Bigert, Johnny. "Automatic and unsupervised methods in natural language processing." Doctoral thesis, Stockholm, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-156.

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Cohn, Trevor A. "Scaling conditional random fields for natural language processing /." Connect to thesis, 2007. http://eprints.unimelb.edu.au/archive/00002874.

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