Relevant bibliographies by topics / Dirichlet modeling / Dissertations / Theses
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Dissertations / Theses on the topic 'Dirichlet modeling'

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Published: 21 December 2024

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1

Heaton, Matthew J. "Temporally Correlated Dirichlet Processes in Pollution Receptor Modeling." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1861.pdf.

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Hu, Zhen. "Modeling photonic crystal devices by Dirichlet-to-Neumann maps /." access full-text access abstract and table of contents, 2009. http://libweb.cityu.edu.hk/cgi-bin/ezdb/thesis.pl?phd-ma-b30082559f.pdf.

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Thesis (Ph.D.)--City University of Hong Kong, 2009.<br>"Submitted to Department of Mathematics in partial fulfillment of the requirements for the degree of Doctor of Philosophy." Includes bibliographical references (leaves [85]-91)
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3

Gao, Wenyu. "Advanced Nonparametric Bayesian Functional Modeling." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/99913.

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Functional analyses have gained more interest as we have easier access to massive data sets. However, such data sets often contain large heterogeneities, noise, and dimensionalities. When generalizing the analyses from vectors to functions, classical methods might not work directly. This dissertation considers noisy information reduction in functional analyses from two perspectives: functional variable selection to reduce the dimensionality and functional clustering to group similar observations and thus reduce the sample size. The complicated data structures and relations can be easily modele
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Monson, Rebecca Lee. "Modeling Transition Probabilities for Loan States Using a Bayesian Hierarchical Model." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd2179.pdf.

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lim, woobeen. "Bayesian Semiparametric Joint Modeling of Longitudinal Predictors and Discrete Outcomes." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1618955725276958.

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Domingues, Rémi. "Probabilistic Modeling for Novelty Detection with Applications to Fraud Identification." Electronic Thesis or Diss., Sorbonne université, 2019. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2019SORUS473.pdf.

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La détection de nouveauté est le problème non supervisé d’identification d’anomalies dans des données de test qui diffèrent de manière significative des données d’apprentissage. La représentation de données temporelles ou de données de types mixtes, telles des données numériques et catégorielles, est une tâche complexe. Outre le type de données supporté, l'efficacité des méthodes de détection de nouveauté repose également sur la capacité à dissocier avec précision les anomalies des échantillons nominaux, l'interprétabilité, la scalabilité et la robustesse aux anomalies présentes dans les donné
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Race, Jonathan Andrew. "Semi-parametric Survival Analysis via Dirichlet Process Mixtures of the First Hitting Time Model." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu157357742741077.

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8

Huo, Shuning. "Bayesian Modeling of Complex High-Dimensional Data." Diss., Virginia Tech, 2020. http://hdl.handle.net/10919/101037.

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With the rapid development of modern high-throughput technologies, scientists can now collect high-dimensional complex data in different forms, such as medical images, genomics measurements. However, acquisition of more data does not automatically lead to better knowledge discovery. One needs efficient and reliable analytical tools to extract useful information from complex datasets. The main objective of this dissertation is to develop innovative Bayesian methodologies to enable effective and efficient knowledge discovery from complex high-dimensional data. It contains two parts—the developme
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Liu, Jia. "Heterogeneous Sensor Data based Online Quality Assurance for Advanced Manufacturing using Spatiotemporal Modeling." Diss., Virginia Tech, 2017. http://hdl.handle.net/10919/78722.

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Online quality assurance is crucial for elevating product quality and boosting process productivity in advanced manufacturing. However, the inherent complexity of advanced manufacturing, including nonlinear process dynamics, multiple process attributes, and low signal/noise ratio, poses severe challenges for both maintaining stable process operations and establishing efficacious online quality assurance schemes. To address these challenges, four different advanced manufacturing processes, namely, fused filament fabrication (FFF), binder jetting, chemical mechanical planarization (CMP), and th
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Bui, Quang Vu. "Pretopology and Topic Modeling for Complex Systems Analysis : Application on Document Classification and Complex Network Analysis." Thesis, Paris Sciences et Lettres (ComUE), 2018. http://www.theses.fr/2018PSLEP034/document.

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Les travaux de cette thèse présentent le développement d'algorithmes de classification de documents d'une part, ou d'analyse de réseaux complexes d'autre part, en s'appuyant sur la prétopologie, une théorie qui modélise le concept de proximité. Le premier travail développe un cadre pour la classification de documents en combinant une approche de topicmodeling et la prétopologie. Notre contribution propose d'utiliser des distributions de sujets extraites à partir d'un traitement topic-modeling comme entrées pour des méthodes de classification. Dans cette approche, nous avons étudié deux aspects
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Schulte, Lukas. "Investigating topic modeling techniques for historical feature location." Thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-85379.

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Software maintenance and the understanding of where in the source code features are implemented are two strongly coupled tasks that make up a large portion of the effort spent on developing applications. The concept of feature location investigated in this thesis can serve as a supporting factor in those tasks as it facilitates the automation of otherwise manual searches for source code artifacts. Challenges in this subject area include the aggregation and composition of a training corpus from historical codebase data for models as well as the integration and optimization of qualified topic mo
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Hu, Xuequn. "Modeling Endogenous Treatment Eects with Heterogeneity: A Bayesian Nonparametric Approach." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3159.

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This dissertation explores the estimation of endogenous treatment effects in the presence of heterogeneous responses. A Bayesian Nonparametric approach is taken to model the heterogeneity in treatment effects. Specifically, I adopt the Dirichlet Process Mixture (DPM) model to capture the heterogeneity and show that DPM often outperforms Finite Mixture Model (FMM) in providing more flexible function forms and thus better model fit. Rather than fixing the number of components in a mixture model, DPM allows the data and prior knowledge to determine the number of components in the data, thus provi
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Zerkoune, Abbas. "Modélisation de l'incertitude géologique par simulation stochastique de cubes de proportions de faciès : application aux réservoirs pétroliers de type carbonaté ou silico-clastique." Phd thesis, Grenoble 1, 2009. http://www.theses.fr/2009GRE10104.

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Après sa découverte, les choix relatifs au développement d'un gisement se prennent sur la base de représentations incertaines du champ. En effet, sa caractérisation utilise des modèles numériques spatiaux porteurs de l'incertitude liée à la complexité du milieu souterrain. D'ordinaire, les méthodes de simulations stochastiques, qui génèrent des modèles équiprobables du sous-sol, sont supposées les quantifier. Néanmoins, ces images alternatives du champ renvoient à des tirages au sein d'un modèle probabiliste unique. Elles oublient l'incertitude relative au choix du modèle probabiliste sous-jac
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Zerkoune, Abbas. "Modélisation de l'incertitude géologique par simulation stochastique de cubes de proportions de faciès - Application aux réservoirs pétroliers de type carbonaté ou silico-clastique." Phd thesis, Université Joseph Fourier (Grenoble), 2009. http://tel.archives-ouvertes.fr/tel-00410136.

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Après sa découverte, les choix relatifs au développement d'un gisement se prennent sur la base de représentations incertaines du champ. En effet, sa caractérisation utilise des modèles numériques spatiaux porteurs de l'incertitude liée à la complexité du milieu souterrain. D'ordinaire, les méthodes de simulations stochastiques, qui génèrent des modèles équiprobables du sous-sol, sont supposées les quantifier. Néanmoins, ces images alternatives du champ renvoient à des tirages au sein d'un modèle probabiliste unique. Elles oublient l'incertitude relative au choix du modèle probabiliste sous-jac
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Harrysson, Mattias. "Neural probabilistic topic modeling of short and messy text." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189532.

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Exploring massive amount of user generated data with topics posits a new way to find useful information. The topics are assumed to be “hidden” and must be “uncovered” by statistical methods such as topic modeling. However, the user generated data is typically short and messy e.g. informal chat conversations, heavy use of slang words and “noise” which could be URL’s or other forms of pseudo-text. This type of data is difficult to process for most natural language processing methods, including topic modeling. This thesis attempts to find the approach that objectively give the better topics from
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Simonnet, Titouan. "Apprentissage et réseaux de neurones en tomographie par diffraction de rayons X. Application à l'identification minéralogique." Electronic Thesis or Diss., Orléans, 2024. http://www.theses.fr/2024ORLE1033.

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La compréhension du comportement chimique et mécanique des matériaux compactés (par exemple sol, sous-sol, matériaux ouvragés) nécessite de se baser sur une description quantitative de structuration du matériau, et en particulier de la nature des différentes phases minéralogiques et de leur relation spatiale. Or, les matériaux naturels sont composés de nombreux minéraux de petite taille, fréquemment mixés à petite échelle. Les avancées récentes en tomographie de diffraction des rayons X sur source synchrotron (à différencier de la tomographie en contraste de phase) permettent maintenant d'obte
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Johansson, Richard, and Heino Otto Engström. "Topic propagation over time in internet security conferences : Topic modeling as a tool to investigate trends for future research." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177748.

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When conducting research, it is valuable to find high-ranked papers closely related to the specific research area, without spending too much time reading insignificant papers. To make this process more effective an automated process to extract topics from documents would be useful, and this is possible using topic modeling. Topic modeling can also be used to provide topic trends, where a topic is first mentioned, and who the original author was. In this paper, over 5000 articles are scraped from four different top-ranked internet security conferences, using a web scraper built in Python. From
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18

Malsiner-Walli, Gertraud, Sylvia Frühwirth-Schnatter, and Bettina Grün. "Model-based clustering based on sparse finite Gaussian mixtures." Springer, 2016. http://dx.doi.org/10.1007/s11222-014-9500-2.

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In the framework of Bayesian model-based clustering based on a finite mixture of Gaussian distributions, we present a joint approach to estimate the number of mixture components and identify cluster-relevant variables simultaneously as well as to obtain an identified model. Our approach consists in specifying sparse hierarchical priors on the mixture weights and component means. In a deliberately overfitting mixture model the sparse prior on the weights empties superfluous components during MCMC. A straightforward estimator for the true number of components is given by the most frequent number
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Lindgren, Jennifer. "Evaluating Hierarchical LDA Topic Models for Article Categorization." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167080.

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With the vast amount of information available on the Internet today, helping users find relevant content has become a prioritized task in many software products that recommend news articles. One such product is Opera for Android, which has a news feed containing articles the user may be interested in. In order to easily determine what articles to recommend, they can be categorized by the topics they contain. One approach of categorizing articles is using Machine Learning and Natural Language Processing (NLP). A commonly used model is Latent Dirichlet Allocation (LDA), which finds latent topics
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Le, Hai-Son Phuoc. "Probabilistic Models for Collecting, Analyzing, and Modeling Expression Data." Research Showcase @ CMU, 2013. http://repository.cmu.edu/dissertations/245.

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Advances in genomics allow researchers to measure the complete set of transcripts in cells. These transcripts include messenger RNAs (which encode for proteins) and microRNAs, short RNAs that play an important regulatory role in cellular networks. While this data is a great resource for reconstructing the activity of networks in cells, it also presents several computational challenges. These challenges include the data collection stage which often results in incomplete and noisy measurement, developing methods to integrate several experiments within and across species, and designing methods th
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Apelthun, Catharina. "Topic modeling on a classical Swedish text corpus of prose fiction : Hyperparameters’ effect on theme composition and identification of writing style." Thesis, Uppsala universitet, Statistiska institutionen, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-441653.

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A topic modeling method, smoothed Latent Dirichlet Allocation (LDA) is applied on a text corpus data of classical Swedish prose fiction. The thesis consists of two parts. In the first part, a smoothed LDA model is applied to the corpus, investigating how changes in hyperparameter values affect the topics in terms of distribution of words within topics and topics within novels. In the second part, two smoothed LDA models are applied to a reduced corpus, only consisting of adjectives. The generated topics are examined to see if they are more likely to occur in a text of a particular author and i
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Khan, Mohammed Salman. "A Topic Modeling approach for Code Clone Detection." UNF Digital Commons, 2019. https://digitalcommons.unf.edu/etd/874.

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In this thesis work, the potential benefits of Latent Dirichlet Allocation (LDA) as a technique for code clone detection has been described. The objective is to propose a language-independent, effective, and scalable approach for identifying similar code fragments in relatively large software systems. The main assumption is that the latent topic structure of software artifacts gives an indication of the presence of code clones. It can be hypothesized that artifacts with similar topic distributions contain duplicated code fragments and to prove this hypothesis, an experimental investigation usi
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Park, Kyoung Jin. "Generating Thematic Maps from Hyperspectral Imagery Using a Bag-of-Materials Model." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1366296426.

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SUI, ZHENHUAN. "Hierarchical Text Topic Modeling with Applications in Social Media-Enabled Cyber Maintenance Decision Analysis and Quality Hypothesis Generation." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1499446404436637.

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Cedervall, Andreas, and Daniel Jansson. "Topic classification of Monetary Policy Minutes from the Swedish Central Bank." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-240403.

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Over the last couple of years, Machine Learning has seen a very high increase in usage. Many previously manual tasks are becoming automated and it stands to reason that this development will continue in an incredible pace. This paper builds on the work in Topic Classification and attempts to provide a baseline on how to analyse the Swedish Central Bank Minutes and gather information using both Latent Dirichlet Allocation and a simple Neural Networks. Topic Classification is done on Monetary Policy Minutes from 2004 to 2018 to find how the distributions of topics change over time. The results a
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Schneider, Bruno. "Visualização em multirresolução do fluxo de tópicos em coleções de texto." reponame:Repositório Institucional do FGV, 2014. http://hdl.handle.net/10438/11745.

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Submitted by Bruno Schneider (bruno.sch@gmail.com) on 2014-05-08T17:46:04Z No. of bitstreams: 1 dissertacao_bruno_schneider.pdf.pdf: 8019497 bytes, checksum: 70ff1fddb844b630666397e95c188672 (MD5)<br>Approved for entry into archive by Janete de Oliveira Feitosa (janete.feitosa@fgv.br) on 2014-05-13T12:56:21Z (GMT) No. of bitstreams: 1 dissertacao_bruno_schneider.pdf.pdf: 8019497 bytes, checksum: 70ff1fddb844b630666397e95c188672 (MD5)<br>Approved for entry into archive by Marcia Bacha (marcia.bacha@fgv.br) on 2014-05-14T19:44:51Z (GMT) No. of bitstreams: 1 dissertacao_bruno_schneider.pdf.pd
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Moon, Gordon Euhyun. "Parallel Algorithms for Machine Learning." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1561980674706558.

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Chiron, Guillaume. "Système complet d’acquisition vidéo, de suivi de trajectoires et de modélisation comportementale pour des environnements 3D naturellement encombrés : application à la surveillance apicole." Thesis, La Rochelle, 2014. http://www.theses.fr/2014LAROS030/document.

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Ce manuscrit propose une approche méthodologique pour la constitution d’une chaîne complète de vidéosurveillance pour des environnements naturellement encombrés. Nous identifions et levons un certain nombre de verrous méthodologiques et technologiques inhérents : 1) à l’acquisition de séquences vidéo en milieu naturel, 2) au traitement d’images, 3) au suivi multi-cibles, 4) à la découverte et la modélisation de motifs comportementaux récurrents, et 5) à la fusion de données. Le contexte applicatif de nos travaux est la surveillance apicole, et en particulier, l’étude des trajectoires des abeil
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Ladouceur, Martin. "Modelling continuous digagnostic test data using Dirichlet process prios distributions." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=95623.

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Diagnostic tests are widely used in medicine and epidemiology. Most diagnostic tests areimperfect at distinguishing subjects with and without the condition of interest, and manythat provide results on a continuous scale have overlapping densities from diseased andnon-diseased subjects. For the se continuous tests, most statistical techniques developed todate assume a parametric (e.g. normal) family for the distribution of the continuousoutcomes within groups, an often unverifiable but convenient distributional assumption.In addition, evaluating the properties of these tests typically requires
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Jaradat, Shatha. "OLLDA: Dynamic and Scalable Topic Modelling for Twitter : AN ONLINE SUPERVISED LATENT DIRICHLET ALLOCATION ALGORITHM." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177535.

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Providing high quality of topics inference in today's large and dynamic corpora, such as Twitter, is a challenging task. This is especially challenging taking into account that the content in this environment contains short texts and many abbreviations. This project proposes an improvement of a popular online topics modelling algorithm for Latent Dirichlet Allocation (LDA), by incorporating supervision to make it suitable for Twitter context. This improvement is motivated by the need for a single algorithm that achieves both objectives: analyzing huge amounts of documents, including new docume
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Habli, Nada. "Nonparametric Bayesian Modelling in Machine Learning." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/34267.

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Nonparametric Bayesian inference has widespread applications in statistics and machine learning. In this thesis, we examine the most popular priors used in Bayesian non-parametric inference. The Dirichlet process and its extensions are priors on an infinite-dimensional space. Originally introduced by Ferguson (1983), its conjugacy property allows a tractable posterior inference which has lately given rise to a significant developments in applications related to machine learning. Another yet widespread prior used in nonparametric Bayesian inference is the Beta process and its extensions. It has
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Halmann, Marju. "Email Mining Classifier : The empirical study on combining the topic modelling with Random Forest classification." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-14710.

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Filtering out and replying automatically to emails are of interest to many but is hard due to the complexity of the language and to dependencies of background information that is not present in the email itself. This paper investigates whether Latent Dirichlet Allocation (LDA) combined with Random Forest classifier can be used for the more general email classification task and how it compares to other existing email classifiers. The comparison is based on the literature study and on the empirical experimentation using two real-life datasets. Firstly, a literature study is performed to gain ins
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Déhaye, Vincent. "Characterisation of a developer’s experience fields using topic modelling." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-171946.

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Finding the most relevant candidate for a position represents an ubiquitous challenge for organisations. It can also be arduous for a candidate to explain on a concise resume what they have experience with. Due to the fact that the candidate usually has to select which experience to expose and filter out some of them, they might not be detected by the person carrying out the search, whereas they were indeed having the desired experience. In the field of software engineering, developing one's experience usually leaves traces behind: the code one produced. This project explores approaches to tac
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Chazel, Florent. "Influence de la topographie sur les ondes de surface." Phd thesis, Université Sciences et Technologies - Bordeaux I, 2007. http://tel.archives-ouvertes.fr/tel-00200419.

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Dans cette thèse, nous considérons le problème d'Euler surface libre sur un domaine à fond non plat, dans le cadre du régime d'ondes longues de faible amplitude. L'objectif est de construire, justifier et comparer de nouveaux modèles asymptotiques pour ce problème, permettant de prendre en compte les effets liés aux variations bathymétriques. En premier lieu, nous construisons rigoureusement deux classes de modèles de Boussinesq symétriques dans le cadre de deux régimes topographiques distincts, celui de faible variations bathymétriques et celui de fortes variations. Dans un second temps, nous
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Bakharia, Aneesha. "Interactive content analysis : evaluating interactive variants of non-negative Matrix Factorisation and Latent Dirichlet Allocation as qualitative content analysis aids." Thesis, Queensland University of Technology, 2014. https://eprints.qut.edu.au/76535/1/Aneesha_Bakharia_Thesis.pdf.

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This thesis addressed issues that have prevented qualitative researchers from using thematic discovery algorithms. The central hypothesis evaluated whether allowing qualitative researchers to interact with thematic discovery algorithms and incorporate domain knowledge improved their ability to address research questions and trust the derived themes. Non-negative Matrix Factorisation and Latent Dirichlet Allocation find latent themes within document collections but these algorithms are rarely used, because qualitative researchers do not trust and cannot interact with the themes that are automat
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Aspilaire, Roseman. "Économie informelle en Haïti, marché du travail et pauvreté : analyses quantitatives." Thesis, Paris Est, 2017. http://www.theses.fr/2017PESC0122/document.

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La prédominance de l’informel dans l’économie d’Haïti, où plus de 80% de la population vit en dessous du seuil de la pauvreté et plus de 35% au chômage, laisse entrevoir des liens étroits entre l’économie informelle, la pauvreté et le marché du travail. Faire ressortir ces interrelations, exige une évaluation de cette économie informelle qui fait l’objet des quatre chapitres de notre thèse traitant successivement l’évolution de la situation macroéconomique, le capital humain, les gains des travailleurs informels, et la segmentation du marché du travail.Le premier chapitre fait un diagnostic du
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White, Nicole. "Bayesian mixtures for modelling complex medical data : a case study in Parkinson’s disease." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/48202/1/Nicole_White_Thesis.pdf.

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Mixture models are a flexible tool for unsupervised clustering that have found popularity in a vast array of research areas. In studies of medicine, the use of mixtures holds the potential to greatly enhance our understanding of patient responses through the identification of clinically meaningful clusters that, given the complexity of many data sources, may otherwise by intangible. Furthermore, when developed in the Bayesian framework, mixture models provide a natural means for capturing and propagating uncertainty in different aspects of a clustering solution, arguably resulting in richer an
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Ficapal, Vila Joan. "Anemone: a Visual Semantic Graph." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-252810.

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Semantic graphs have been used for optimizing various natural language processing tasks as well as augmenting search and information retrieval tasks. In most cases these semantic graphs have been constructed through supervised machine learning methodologies that depend on manually curated ontologies such as Wikipedia or similar. In this thesis, which consists of two parts, we explore in the first part the possibility to automatically populate a semantic graph from an ad hoc data set of 50 000 newspaper articles in a completely unsupervised manner. The utility of the visual representation of th
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GIOVANNINI, STEFANO. "Verso un indice "convergente" dell'impatto dei prodotti culturali italiani in Cina." Doctoral thesis, Università Cattolica del Sacro Cuore, 2022. http://hdl.handle.net/10280/122043.

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La tesi muove dall’ipotesi che sia possibile costruire un modello predittivo del successo di un prodotto mediale italiano sul mercato cinese, laddove per “successo” s’intenda un impatto culturale ed economico pari a quello di alcuni prodotti benchmark degli ultimi anni (il romanzo L’amica geniale, il film Perfetti sconosciuti, la serie TV My Brilliant Friend). L’impatto culturale è misurato come generazione di discorso online e quello economico con indicatori sia tradizionali, nel caso della distribuzione fisica, sia digitali nel caso di quella online. I tre casi usati come benchmark hanno avu
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Mercado, Salazar Jorge Anibal, and S. M. Masud Rana. "A Confirmatory Analysis for Automating the Evaluation of Motivation Letters to Emulate Human Judgment." Thesis, Högskolan Dalarna, Institutionen för information och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-37469.

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Manually reading, evaluating, and scoring motivation letters as part of the admissions process is a time-consuming and tedious task for Dalarna University's program managers. An automated scoring system would provide them with relief as well as the ability to make much faster decisions when selecting applicants for admission. The aim of this thesis was to analyse current human judgment and attempt to emulate it using machine learning techniques. We used various topic modelling methods, such as Latent Dirichlet Allocation and Non-Negative Matrix Factorization, to find the most interpretable top
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Patel, Virashree Hrushikesh. "Topic modeling using latent dirichlet allocation on disaster tweets." 2018. http://hdl.handle.net/2097/39337.

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Master of Science<br>Department of Computer Science<br>Cornelia Caragea<br>Doina Caragea<br>Social media has changed the way people communicate information. It has been noted that social media platforms like Twitter are increasingly being used by people and authorities in the wake of natural disasters. The year 2017 was a historic year for the USA in terms of natural calamities and associated costs. According to NOAA (National Oceanic and Atmospheric Administration), during 2017, USA experienced 16 separate billion-dollar disaster events, including three tropical cyclones, eight severe storms,
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Lin, Chieh-Hung, and 林桀宏. "Survey Topic Modeling and Expert Finding Based on Latent Dirichlet Allocation." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/7f8879.

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碩士<br>國立臺灣科技大學<br>資訊工程系<br>99<br>To get into a new research topic for a researcher, it is a shortcut to study survey articles that provide some benefits for readers. Survey articles introduce and summarize significant approaches from those important articles of a certain research topic. Users get these to understand corresponding domains easily, and find related papers quickly. However, it is not easy to find survey articles in every research domain, or there are no recent survey articles in a specific domain. To deal with this in actual condition, traditional approaches use citing texts to genera
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Crea, Catherine. "On the Robustness of Dirichlet-multinomial Regression in the Context of Modeling Pollination Networks." Thesis, 2011. http://hdl.handle.net/10214/3222.

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Recent studies have suggested that the structure of plant-pollinator networks is driven by two opposing theories: neutrality and linkage rules. However, relatively few studies have tried to exploit both of these theories in building pollination webs. This thesis proposes Dirichlet-Multinomial (DM) regression to model plant-pollinator interactions as a function of plant-pollinator characteristics (e.g. complementary phenotypic traits), for evaluating the contribution of each process to network structure. DM regression models first arose in econometrics for modeling consumers' choice behaviour
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Wei, Hongchuan. "Sensor Planning for Bayesian Nonparametric Target Modeling." Diss., 2016. http://hdl.handle.net/10161/12863.

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<p>Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements u
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Hines, Keegan. "Bayesian approaches for modeling protein biophysics." Thesis, 2014. http://hdl.handle.net/2152/26016.

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Proteins are the fundamental unit of computation and signal processing in biological systems. A quantitative understanding of protein biophysics is of paramount importance, since even slight malfunction of proteins can lead to diverse and severe disease states. However, developing accurate and useful mechanistic models of protein function can be strikingly elusive. I demonstrate that the adoption of Bayesian statistical methods can greatly aid in modeling protein systems. I first discuss the pitfall of parameter non-identifiability and how a Bayesian approach to modeling can yield reliable and
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46

"Bayesian Nonparametric Modeling and Inference for Multiple Object Tracking." Doctoral diss., 2019. http://hdl.handle.net/2286/R.I.54996.

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abstract: The problem of multiple object tracking seeks to jointly estimate the time-varying cardinality and trajectory of each object. There are numerous challenges that are encountered in tracking multiple objects including a time-varying number of measurements, under varying constraints, and environmental conditions. In this thesis, the proposed statistical methods integrate the use of physical-based models with Bayesian nonparametric methods to address the main challenges in a tracking problem. In particular, Bayesian nonparametric methods are exploited to efficiently and robustly infer ob
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Karlsson, Kalle. "News media attention in Climate Action: Latent topics and open access." Thesis, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:hb:diva-23413.

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The purpose of the thesis is i) to discover the latent topics of SDG13 and their coverage in news media ii) to investigate the share of OA and Non-OA articles and reviews in each topic iii) to compare the share of different OA types (Green, Gold, Hybrid and Bronze) in each topic. It imposes a heuristic perspective and explorative approach in reviewing the three concepts open access, altmetrics and climate action (SDG13). Data is collected from SciVal, Unpaywall, Altmetric.com and Scopus rendering a dataset of 70,206 articles and reviews published between 2014-2018. The documents retrieved are
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Ely, Nicole. "Rekonstrukce identit ve fake news: Srovnání dvou webových stránek s obsahem fake news." Master's thesis, 2020. http://www.nusl.cz/ntk/nusl-415291.

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TOPICAL ANALYSIS OF FAKE NEWS 4 Abstract Since the 2016 US presidential campaign of Donald Trump, the term "fake news" has permeated mainstream discourse. The proliferation of disinformation and false narratives on social media platforms has caused concern in security circles in both the United States and European Union. Combining latent Dirichlet allocation, a machine learning method for text mining, with themes on topical analysis, ideology and social identity drawn from Critical Discourse theory, this thesis examines the elaborate fake news environments of two well-known English language we
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Ji, Chunlin. "Advances in Bayesian Modelling and Computation: Spatio-Temporal Processes, Model Assessment and Adaptive MCMC." Diss., 2009. http://hdl.handle.net/10161/1609.

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<p>The modelling and analysis of complex stochastic systems with increasingly large data sets, state-spaces and parameters provides major stimulus to research in Bayesian nonparametric methods and Bayesian computation. This dissertation presents advances in both nonparametric modelling and statistical computation stimulated by challenging problems of analysis in complex spatio-temporal systems and core computational issues in model fitting and model assessment. The first part of the thesis, represented by chapters 2 to 4, concerns novel, nonparametric Bayesian mixture models for spatial point
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