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 185 for “"Text mining"”.
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Contextual text mining
With the dramatic growth of text information, there is an increasing need for powerful text mining systems that can automatically discover useful knowledge from text. Text is generally associated with all kinds of contextual information. Those contexts can be explicit, such as the time and the …
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Bridging Text Mining and Bayesian Networks
… as and when new data is observed. Literature mining is a very important source of this new data. In this work, we explore what kind of data needs to be extracted with the view to update Bayesian Networks, existing technologies which can be useful in achieving some of the goals and what …
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Structure-enhanced text mining for science
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-03-28 without embargo terms
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How to Rank Answers in Text Mining
In this thesis, we mainly focus on case studies about answers. We present the methodology CEW-DTW and assess its performance about ranking quality. Based on the CEW-DTW, we improve this methodology by combining Kullback-Leibler divergence with CEW-DTW, since Kullback-Leibler divergence can check …
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Bayesian nonparametric learning for complicated text mining
Text mining has gained the ever-increasing attention of researchers in recent years because text is one of the most natural and easy ways to express human knowledge and opinions, and is therefore believed to have a variety of application scenarios and a potentially high commercial value. It is …
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Text mining with neural network and MapReduce
… One of these application is doing data mining (text mining) to analyze customers' sentiment from their reviews' text. This research aims to investigate and classify polarity of customer's reviews as positive or negative opinion. While other studies in this field focused on support vector …
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Beyond topic-based representations for text mining
… amount of online information is natural language text: newspapers, blog articles, forum posts and comments, tweets, scientific literature, government documents, and more. While in general, all kinds of online information is useful, textual information is especially important—it is the most …
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Semantic text classification for cancer text mining
… researchers and oncologists benefit greatly from text mining major knowledge sources in biomedicine such as PubMed. Fundamentally, text mining depends on accurate text classification. In conventional natural language processing (NLP), this requires experts to annotate scientific text, which is …
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Cognition-based approaches for high-precision text mining
… of information extraction from free-form text via the use of cognitive-based approaches to natural language processing (NLP). Cognitive-based approaches are an important, and relatively new, area of research in NLP and search, as well as linguistics. Cognitive approaches enable significant …
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Weakly supervised text mining with text-rich networks
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms
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Text mining and its applications in food safety
This Dissertation was approved for publication on 2021-06-22 at 12:53.
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Manufacturing variability; effects and characterization through text-mining
Researchers and developers of new materials and processes often underestimate or neglect the effects of manufacturing variability and, as a result, make overly optimistic assumptions about their technologies. In this thesis, I explore the effects of manufacturing variability and find ways to …
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VISUAL ANALYTICS FOR OPEN-ENDED TASKS IN TEXT MINING
… identify clusters by assigning attributes and examining the resulting distributions. ParallelSpaces examines the understanding of topic modeling applied to Yelp business reviews, where businesses and their reviews each constitute a separate visual space. Exploring these spaces enables the …
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Advancing sustainability indicators through text mining: a feasibility demonstration
… unstructured digital news articles with text mining methods. Using San Mateo County, California, as a case study, a non-mutually exclusive supervised classification algorithm with natural language processing techniques is applied to analyze sustainability content in news articles and …
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Integrative text mining and management in multidimensional text databases
As the text information grows explosively in today's multidimensional text databases, managing and mining this kind of databases is now playing an extremely important role in every domain. Different from traditional text mining tasks that target at single data sets, a text management system for a …
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Text mining with word embedding for outlier and sentiment analysis
… easy to collect and store massive text data in various domains such as online social networks, medical records and news reports. In contrast to the gigantic volume of text data, human capabilities to read and process text data is limited. Hence, there is an emerging demand for …
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Using Dependency Parses to Augment Feature Construction for Text Mining
… unstructured information in the form of text, there is now an increased emphasis on text mining. A broad range of techniques are now used for text mining, including algorithms adapted from machine learning, NLP, computational linguistics, and data mining. Applications are also multi-fold, …
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Una aproximación al Riesgo Reputacional Bancario mediante técnicas de Text Mining
… información suministrada por el mercado, el contexto macroeconómico local y la percepción de los distintos participantes. Ante la falta de regulación específica, esta tesis es una propuesta para mitigar el riesgo reputacional de las Entidades Financieras y por lo tanto, da respuesta a una …
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Text mining at multiple granularity: leveraging subwords, words, phrases, and sentences
… digitization of information, large quantities of text-heavy data is being constantly generated in many languages and across domains such as web documents, research papers, business reviews, news, and social posts. As such, efficiently and effectively searching, organizing, and extracting …
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