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Relevant bibliographies by topics / Informational Text Features / Dissertations / Theses

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Dissertations / Theses on the topic 'Informational Text Features'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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1

Neal, Ted A. "The impact of argument-based learning environments on early learners multimodal representations." Diss., University of Iowa, 2017. https://ir.uiowa.edu/etd/5578.

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The purpose of this study was to examine the impact of an immersive argument based learning environment on students’ multimodal competencies. The objective was to study the impact on students learning as they engage in an ABI classroom, centered on the SWH approach, when compared to students in traditional classrooms. Summary writing samples were collected and coded for informational text features which allowed us to understand cohesion with the learners. Additionally, we were able to study these impacts longitudinally, measuring teacher experience and student exposure to this learning environ

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2

Oyarce, Guillermo Alfredo. "A Study of Graphically Chosen Features for Representation of TREC Topic-Document Sets." Thesis, University of North Texas, 2000. https://digital.library.unt.edu/ark:/67531/metadc2456/.

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Document representation is important for computer-based text processing. Good document representations must include at least the most salient concepts of the document. Documents exist in a multidimensional space that difficult the identification of what concepts to include. A current problem is to measure the effectiveness of the different strategies that have been proposed to accomplish this task. As a contribution towards this goal, this dissertation studied the visual inter-document relationship in a dimensionally reduced space. The same treatment was done on full text and on three docum

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Rogers, Benjamin Charles. "Using Genetic Algorithms for Feature Set Selection in Text Mining." Miami University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=miami1389811705.

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4

Barjasteh, Delforooz Behrooz. "Discourse Features in Balochi of Sistan : (Oral Narratives)." Doctoral thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-129832.

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This work presents a first study of discourse features in Balochi narratives of Sistan. Discourse analysis investigates what are the properties that make for well-formed texts in a language. There are many approaches to discourse analysis and most approaches focus on a particular aspect of text formation. The approach to text linguistics or discourse analysis taken in this work is based on Dooley and Levinsohn’s Analyzing Discourse: A manual of basic concepts (2001). Their methodology has been refined over years of practical use and, among diverse methodologies, they follow a functional and co

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5

Levefeldt, Christer. "Evaluation of NETtalk as a means to extract phonetic features from text for synchronization with speech." Thesis, University of Skövde, Department of Computer Science, 1998. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-173.

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<p>The background for this project is a wish to automate synchronization of text and speech. The idea is to present speech through speakers synchronized word-for-word with text appearing on a monitor.</p><p>The solution decided upon is to use artificial neural networks, ANNs, to convert both text and speech into streams made up of sets of phonetic features and then matching these two streams against each other. Several text-to-feature ANN designs based on the NETtalk system are implemented and evaluated. The extraction of phonetic features from speech and the synchronization itself are not imp

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6

Islam, Mohammad Zahurul Verfasser], Alexander [Akademischer Betreuer] Mehler, Visvanathan [Akademischer Betreuer] Ramesh, Detlef [Akademischer Betreuer] [Krömker, and Manfred [Akademischer Betreuer] Schmidt-Schauß. "Multilingual text classification using information-theoretic features / Mohammad Zahurul Islam. Betreuer: Alexander Mehler ; Visvanathan Ramesh. Gutachter: Detlef Krömker ; Manfred Schmidt-Schauß." Frankfurt am Main : Univ.-Bibliothek Frankfurt am Main, 2015. http://d-nb.info/1077557639/34.

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Islam, Zahurul [Verfasser], Alexander Akademischer Betreuer] Mehler, Visvanathan [Akademischer Betreuer] Ramesh, Detlef [Akademischer Betreuer] [Krömker, and Manfred [Akademischer Betreuer] Schmidt-Schauß. "Multilingual text classification using information-theoretic features / Mohammad Zahurul Islam. Betreuer: Alexander Mehler ; Visvanathan Ramesh. Gutachter: Detlef Krömker ; Manfred Schmidt-Schauß." Frankfurt am Main : Univ.-Bibliothek Frankfurt am Main, 2015. http://d-nb.info/1077557639/34.

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8

Koka, Keerthika. "Feature Selection through Visualisation for the Classification of Online Reviews." Thesis, Purdue University, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10278441.

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<p> The purpose of this work is to prove that the visualization is at least as powerful as the best automatic feature selection algorithms. This is achieved by applying our visualization technique to the online review classication into fake and genuine reviews. Our technique uses radial chart and the color overlaps to explore the best feature selection through visualization for classication. Every review is treated as a radial translucent red or blue membrane with its dimensions determining the shape of the membrane. This work also shows how the dimension ordering and combination is relevant i

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9

Schön, Ragnar. "A cross-cultural listener-based study on perceptual features in K-pop." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-178018.

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Recent research within the Music Information Retrieval (MIR) field has shown the relevance of perceptual features for musical signals. The idea is to identify a small set of features that are natural descriptions from a perceptual perspective. The notion of perceptual features is based on the ecological approach to music, that is, focussing on sound events rather than spectral information. Furthermore, MIR research has had an overemphasis on Western music and listeners. This leads to the question of whether the concept of perceptual features is culturally independent or not. This was investiga

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Rorissa, Abebe. "Perceived features and similarity of images: An investigation into their relationships and a test of Tversky's contrast model." Thesis, University of North Texas, 2005. https://digital.library.unt.edu/ark:/67531/metadc4749/.

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The creation, storage, manipulation, and transmission of images have become less costly and more efficient. Consequently, the numbers of images and their users are growing rapidly. This poses challenges to those who organize and provide access to them. One of these challenges is similarity matching. Most current content-based image retrieval (CBIR) systems which can extract only low-level visual features such as color, shape, and texture, use similarity measures based on geometric models of similarity. However, most human similarity judgment data violate the metric axioms of these models. Tver

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Söderberg, Max Joel, and Axel Meurling. "Feature selection in short-term load forecasting." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-259692.

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This paper investigates correlation between energy consumption 24 hours ahead and features used for predicting energy consumption. The features originate from three categories: weather, time and previous energy. The correlations are calculated using Pearson correlation and mutual information. This resulted in the highest correlated features being those representing previous energy consumption, followed by temperature and month. Two identical feature sets containing all attributes1 were obtained by ranking the features according to correlation. Three feature sets were created manually. The firs

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12

Muhammad, Hanif Shehzad. "Feature selection and classifier combination: Application to the extraction of textual information in scene images." Paris 6, 2009. http://www.theses.fr/2009PA066521.

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Dans cette thèse, nous avons traité le problème de la détection et de la localisation dans les images de scène. Notre système est composé de deux parties : le Détecteur de texte et le Localiseur de texte. Le détecteur de texte (une cascade de classifieurs boostés) emploie la méthode de dopage qui sélectionne et combine des descripteurs et des classifieurs faibles pertinents. Plus précisément, nous avons proposé une version régularisée de l’algorithme AdaBoost qui intègre la complexité (liée à la charge de calcul) des descripteurs et des classifieurs faibles dans la phase de sélection. Nous avo

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13

Dimitriadis, Spyridon. "Multi-task regression QSAR/QSPR prediction utilizing text-based Transformer Neural Network and single-task using feature-based models." Thesis, Linköpings universitet, Statistik och maskininlärning, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-177186.

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With the recent advantages of machine learning in cheminformatics, the drug discovery process has been accelerated; providing a high impact in the field of medicine and public health. Molecular property and activity prediction are key elements in the early stages of drug discovery by helping prioritize the experiments and reduce the experimental work. In this thesis, a novel approach for multi-task regression using a text-based Transformer model is introduced and thoroughly explored for training on a number of properties or activities simultaneously. This multi-task regression with Transformer

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Dang, Quoc Bao. "Information spotting in huge repositories of scanned document images." Thesis, La Rochelle, 2018. http://www.theses.fr/2018LAROS024/document.

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Ce travail vise à développer un cadre générique qui est capable de produire des applications de localisation d'informations à partir d’une caméra (webcam, smartphone) dans des très grands dépôts d'images de documents numérisés et hétérogènes via des descripteurs locaux. Ainsi, dans cette thèse, nous proposons d'abord un ensemble de descripteurs qui puissent être appliqués sur des contenus aux caractéristiques génériques (composés de textes et d’images) dédié aux systèmes de recherche et de localisation d'images de documents. Nos descripteurs proposés comprennent SRIF, PSRIF, DELTRIF et SSKSRIF

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Cleve, Oscar, and Sara Gustafsson. "Automatic Feature Extraction for Human Activity Recognitionon the Edge." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260247.

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This thesis evaluates two methods for automatic feature extraction to classify the accelerometer data of periodic and sporadic human activities. The first method selects features using individual hypothesis tests and the second one is using a random forest classifier as an embedded feature selector. The hypothesis test was combined with a correlation filter in this study. Both methods used the same initial pool of automatically generated time series features. A decision tree classifier was used to perform the human activity recognition task for both methods.The possibility of running the devel

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Wan, Zhibin, and Huatai Xu. "Performance comparison of different machine learningmodels in detecting fake news." Thesis, Högskolan Dalarna, Institutionen för information och teknik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:du-37576.

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The phenomenon of fake news has a significant impact on our social life, especially in the political world. Fake news detection is an emerging area of research. The sharing of infor-mation on the Web, primarily through Web-based online media, is increasing. The ability to identify, evaluate, and process this information is of great importance. Deliberately created disinformation is being generated on the Internet, either intentionally or unintentionally. This is affecting a more significant segment of society that is being blinded by technology. This paper illustrates models and methods for de

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Munnecom, Lorenna, and Miguel Chaves de Lemos Pacheco. "Exploration of an Automated Motivation Letter Scoring System to Emulate Human Judgement." Thesis, Högskolan Dalarna, Mikrodataanalys, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:du-34563.

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As the popularity of the master’s in data science at Dalarna University increases, so does the number of applicants. The aim of this thesis was to explore different approaches to provide an automated motivation letter scoring system which could emulate the human judgement and automate the process of candidate selection. Several steps such as image processing and text processing were required to enable the authors to retrieve numerous features which could lead to the identification of the factors graded by the program managers. Grammatical based features and Advanced textual features were extra

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Artchounin, Daniel. "Tuning of machine learning algorithms for automatic bug assignment." Thesis, Linköpings universitet, Programvara och system, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139230.

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In software development projects, bug triage consists mainly of assigning bug reports to software developers or teams (depending on the project). The partial or total automation of this task would have a positive economic impact on many software projects. This thesis introduces a systematic four-step method to find some of the best configurations of several machine learning algorithms intending to solve the automatic bug assignment problem. These four steps are respectively used to select a combination of pre-processing techniques, a bug report representation, a potential feature selection tec

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19

Ryan, Elisabeth. "Towards word alignment and dataset creation for shorthand documents and transcripts." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-452278.

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Analysing handwritten texts and creating labelled data sets can facilitate novel research on languages and advanced computerized analysis of authors works. However, few handwritten works have word wise labelling or data sets associated with them. More often a transcription of the text is available, but without any exact coupling between words in the transcript and word representations in the document images. Can an algorithm be created that will take only an image of handwritten text and a corresponding transcript and return a partial alignment and data set? An algorithm is developed in this t

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20

Alvarenga, Leonel Diógenes Carvalhaes. "Uso de Seleção de Características da Wikipedia na Classificação Automática de Textos." Universidade Federal de Goiás, 2012. http://repositorio.bc.ufg.br/tede/handle/tde/2870.

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Submitted by Cássia Santos (cassia.bcufg@gmail.com) on 2014-07-31T14:43:10Z No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) uso_de_selecao_de_caracteristicas_da_wikipedia_na_classificacao_automatica_de_textos.pdf: 1449954 bytes, checksum: 9086dec3868b6b703340b550c614d33d (MD5)<br>Made available in DSpace on 2014-07-31T14:43:10Z (GMT). No. of bitstreams: 2 license_rdf: 23148 bytes, checksum: 9da0b6dfac957114c6a7714714b86306 (MD5) uso_de_selecao_de_caracteristicas_da_wikipedia_na_classificacao_automatica_de_textos.pdf: 1449954 bytes, checksum:

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Lee, Pai-Hsun, and 李柏勳. "Identifying Competitor Relationships Using Network Features and Text Information." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/57897065016318741207.

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碩士<br>國立臺灣大學<br>資訊管理學研究所<br>100<br>The business environment is increasingly volatile and turbulent. Organizations must adapt to their environments proactively and swiftly in order to survive and prosper. Environmental scanning can be adopted by organizations to discover varieties of information. Competitor information serves as an important part while conducting environmental scanning. Before gathering the competitor information, competitor mining is a key and necessary task for company that allows a company to shore up their defenses against probable competitive incursions and plan competitiv

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22

Makrehchi, Masoud. "Feature Ranking for Text Classifiers." Thesis, 2007. http://hdl.handle.net/10012/3250.

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Feature selection based on feature ranking has received much attention by researchers in the field of text classification. The major reasons are their scalability, ease of use, and fast computation. %, However, compared to the search-based feature selection methods such as wrappers and filters, they suffer from poor performance. This is linked to their major deficiencies, including: (i) feature ranking is problem-dependent; (ii) they ignore term dependencies, including redundancies and correlation; and (iii) they usually fail in unbalanced data. While using feature ranking methods for dimens

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23

"Semantic Feature Extraction for Narrative Analysis." Doctoral diss., 2016. http://hdl.handle.net/2286/R.I.40243.

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abstract: A story is defined as "an actor(s) taking action(s) that culminates in a resolution(s)''. I present novel sets of features to facilitate story detection among text via supervised classification and further reveal different forms within stories via unsupervised clustering. First, I investigate the utility of a new set of semantic features compared to standard keyword features combined with statistical features, such as density of part-of-speech (POS) tags and named entities, to develop a story classifier. The proposed semantic features are based on <Subject, Verb, Object> triplets tha

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Shen, Yu-Chun, and 沈砡君. "Depression Detection Based on PTT Bulletin Board System: Using Text and Time Information as Features." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/60537428349207021311.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>99<br>Depression is now an important disease in human society, while many people have this problem without being aware of it. Since people like to post their diary or vent emotions on the web, detect depression by texts should be a worthwhile topic. The goal of this thesis is to design a classification system that determines whether a person is a potential candidate for depression given the texts written by the person. To solve this problem, we propose to use a “two-stage” classifier with supervised learning method. The first stage determines whether the target is n

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LIU, YAN-CI, and 劉晏慈. "A Thorough Test of ERP P300-based Features for Analyzing the EEG Data of a Concealed Information Test." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/25jkmr.

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碩士<br>國立中央大學<br>認知與神經科學研究所<br>107<br>The Concealed Information Test (CIT) with P300-based EEG examination has been reported of high performance in differentiating knowledgeable/non-knowledgeable subjects. This study evaluated the efficacy of the P300 peak-to-peak (p-p) magnitude in the detection of the guilty knowledge acquired during mock crime scenarios. Two experiments with different mock crime scenarios were conducted. The mock crime in Experiment 1 was a theft crime, in which participants pretended to steal a critical item and hide it to a designated place. The mock crime in Experiment 2

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26

Jayaratne, Lakshman, University of Western Sydney, College of Health and Science, and School of Computing and Mathematics. "Enhancing retrieval of images on the web through effective use of associated text and semantics from low-level image features." 2006. http://handle.uws.edu.au:8081/1959.7/14187.

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Content-based indexing and retrieval has emerged as an important area in computer vision and multimedia computing. Current solutions for searching image data primarily deal with associated text and low-level image features. Humans tend to use high-level concepts in everyday life; user queries are typically based on higher-level semantics and not low-level image features. However, what current computer vision techniques can automatically extract from images are mostly low-level visual features. To narrow down this semantic gap, some off-line and on-line processing is needed. The state-of-the-ar

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Νασίκας, Ιωάννης. "Text mining : μια νέα προτεινόμενη μέθοδος με χρήση κανόνων συσχέτισης". 2006. http://nemertes.lis.upatras.gr/jspui/handle/10889/518.

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Η εξόρυξη κειμένου (text mining) είναι ένας νέος ερευνητικός τομέας που προσπαθεί να επιλύσει το πρόβλημα της υπερφόρτωσης πληροφοριών με τη χρησιμοποίηση των τεχνικών από την εξόρυξη από δεδομένα (data mining), την μηχανική μάθηση (machine learning), την επεξεργασία φυσικής γλώσσας (natural language processing), την ανάκτηση πληροφορίας (information retrieval), την εξαγωγή πληροφορίας (information extraction) και τη διαχείριση γνώσης (knowledge management). Στο πρώτο μέρος αυτής της διπλωματικής εργασίας αναφερόμαστε αναλυτικά στον καινούριο αυτό ερευνητικό τομέα, διαχωρίζοντάς τον από άλλο

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