Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 45 for “"Document classification"”.
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Nonnegative Matrix Factorization and Document Classification
… paper is concerned with the preprocessing of the documents and how the preprocessing effects document classification. The preprocessing discussed in this paper will run the classification on a variety of inner dimensions to see how my initialization compares to random initialization across an …
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Automatic Document Classification in Small Environments
<p>Document classification is used to sort and label documents. This gives users quicker access to relevant data. Users that work with large inflow of documents spend time filing and categorizing them to allow for easier procurement. The Automatic Classification and Document Filing (ACDF) system …
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Algorithms for Hash Coding and Document Classification
Made available in DSpace on 2014-12-10T20:13:34Z (GMT). No. of bitstreams: 1 7309906.pdf: 2761825 bytes, checksum: f4f94c482f7e19eb6fad9964ab40f0be (MD5) Previous issue date: 1972
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An Exploration of Multimodal Document Classification Strategies
This thesis explores multimodal document classification algorithms in a unified framework. Classification algorithms are designed to exploit both text and image information, which proliferates in modern documents. We design meta-classification schemes that combine and integrate state-of-the-art …
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Modeling document classification to automate mental health diagnosis
… of this study is to determine if diagnosis documents can be used with document classification to automatically diagnose mental health conditions. Document classification allows text documents to be analyzed and organized into their appropriate classes based on the features and words …
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Effective Features and Machine Learning Methods for Document Classification
Document classification has been involved in a variety of applications, such as phishing and fraud detection, news categorisation, and information retrieval. This thesis aims to provide novel solutions to several important problems presented by document classification. First, an improved Principal …
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Document Classification in Support of Automated Metadata Extraction Form Heterogeneous Collections
… laboratories, and companies are placing their documents online and making them searchable via metadata fields such as author, title, and publishing organization. To enable this, every document in the collection must be catalogued using the metadata fields. Though time consuming, the task of …
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Applying Language Models To Patient Health Records: Acronym Expansion, Long Document Classification and Explainable Predictions
The health industry is experiencing a digital transformation, with Electronic Health Records (EHRs) becoming central repositories for an ever-growing volume of patient data. While EHR clinical notes offer rich, detailed insights into patient conditions, treatments and outcomes, extracting …
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A study of automatic email routing for an information technology help desk
Document classification has been a classic problem in both machine learning and information retrieval. One domain for document classification is automatic email routing. Given an email (a document), the system attempts to guess the location that the email should be routed to. An automatic system …
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Concept-based text classification
… of this thesis is to do automatic concept based document classification. Classification or clustering is the process of grouping similar objects together so that they can be effectively retrieved when queried upon. An experimental system that does this concept based document classification is …
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Investigation on Applying Modular Ontology to Statistical Language Model for Information Retrieval
… query expansion (OQE) and ontology-based document classification (ODC). Research experiments have required development of an independent search tool that can combine the OQE and ODC in a traditional SLM-based information retrieval (IR) process using a Web document collection. This research …
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New Weighting Schemes for Document Ranking and Ranked Query Suggestion
… need or the importance of a term to a document. This thesis aims to investigate novel term weighting methods with applications in document representation for text classification, web document ranking, and ranked query suggestion. Firstly, this research proposes a new feature for …
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Examination of machine learning methods for multi-label classification of intellectual property documents
… learning techniques for the task of multi-label document classification applied to a corpus of United States patent grants. The rapidly rising number of patent applications in the past several decades has led to a rising need for enhanced automatic patent processing tools. The task of automated …
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Pushing the limits of traditional unsupervised learning
… success in the supervised learning problem of classification and unsupervised learning problems of feature extraction and cluster analysis, traditional machine learning methods can still provide state-of-the-art performance. In this thesis, a novel clustering framework that combines common …
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Topic specific spider for taxonomic documents
… to develop a subsystem that collects taxonomic documents available on the World Wide Web using a combination of spidering and document classification techniques. To increase the number of documents collected, two query expansion techniques have been considered and evaluated. We found that …
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Robust graph representation learning with structure-aware attention and self-supervised contrastive frameworks.
… and interpretability for node and graph classification tasks. Specifically, I investigate attention-based Graph Neural Networks (GNNs) and their variants, designing structure-aware and contrastive learning strategies to capture both local and global dependencies in graphs. Through …
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Interaction harvesting for document retrieval
… to provide meaningful search terms for non-text documents. Unfortunately, such systems usually require the author to enter the keywords manually, a task that is commonly neglected, or is executed poorly. This thesis proposes an approach to document categorization called Interaction Harvesting, …
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Applications and Analysis of NLP Deep Learning Models for Antibiotic's Side Effects Classifications
… will provide an additional tool for unsupervised document classification. While GWA shows promise in accurately clustering articles, there are some challenges that will need to be researched and refined on other collected or computer-generated datasets before being applied. Future development of …
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