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 39 for “"tf-idf"”.
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IVIS: Search and visualization on heterogeneous information networks
… Hetero-personalized PageRank outperform the TF-IDF ranking or mixture of TF-IDF and authority ranking. Our work opens several directions for future research.
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Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)
… Term Frequency-Inverse Document Frequency (TF-IDF) as the main algorithm in Android malware detection. The TF-IDF algorithm is used to filter Android features filtered before detection process. However, IDF is unaware to the training class labels and gives incorrect weight value to some …
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An unsupervised approach to COVID-19 fake tweet detection
… the ongoing COVID-19 pandemic, social media platforms have become a crucial source of information. However, not all information shared on these platforms is accurate. The dissemination of fake news, intentional or unintentional, can lead to panic among readers and further exacerbate the effects …
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Evaluation of Word and Paragraph Embeddings and Analogical Reasoning as an Alternative to Term Frequency-Inverse Document Frequency-based Classification in Support of Biocuration
… used term frequency-inverse document frequency (TF-IDF ) representation by capturing semantic relations? The analysis measures the quality of sentence classification using term TF-IDF representations, and finds a practical upper limit to precision and recall in a biomedical text classification …
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Knowledge-Guided Machine Learning for Single-Cell Regulatory Genomics
Transcription factors (TFs) and cis-regulatory elements coordinate gene regulation, and single-cell sequencing now enables these programs to be studied at high resolution. However, single-cell RNA-seq and ATAC-seq data are sparse and high-dimensional, making it difficult for existing methods to …
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Machine learning and deep learning techniques for natural language processing with application to audio recordings
… the Term Frequency-Inverse Document Frequency (TF- IDF) and the Count Vectorizer. The study then compared the accuracy of Artificial Neural Network (ANN) and Naïve Bayes classifiers in predicting the employment status of the debtor. To evaluate the performance of the ASR transcription method, …
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New Weighting Schemes for Document Ranking and Ranked Query Suggestion
… term weighting scheme based on term frequency (TF) and the newly proposed feature. The experimental results show that the proposed methods, CSDF and TF-CSDF, improve the performance of document classification in comparison with other widely used VSM document representations. Secondly, a new …
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A Comparative Study on Feature Extraction and Classification/Clustering of Fake News and Conspiracy Theories from Twitter Data
… twitter datasets. The results indicate that the tf-idf method of feature extraction, when implemented with the svm classification algorithm, yields the highest accuracy of 99.6% in comparison to the other algorithms i.e. multinomial naive bayes, logistic regression and decision tree. The Bag of …
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Natural Language Processing and Recommendation Engine for Stack Overflow Data
… Our pipeline consists of document retrieval (TF-IDF and HOTT), text embedding (Sentence BERT), and classification (multi-label and multi-class). We experiment with neural networks and other classifier strategies to identify the most relevant Stack Overflow tags. We then use these tags to …
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Performance analysis of text classification algorithms for PubMed articles
… the Term Frequency Inverse Document Frequency (Tf-idf) technique and topic modelling performed with the objective to ascertain the correlation between assigned topics (unsupervised learning task) and MeSH terms in PubMed. Findings revealed the degree of coupling was low although significant. Of …
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Building a question answering system for the introduction to statistics course using supervised learning techniques
… Term Frequency times Inverse Document Frequency (TF-IDF), Latent Semantic Analysis (LSA), Latent Dirichlet Allocation (LDiA), pre-trained Global Vector (GloVe) word embeddings and customengineered features were also compared. This study found that a model using an MLR classifier with TF-IDF …
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Heike, Jike, Chuangke : creativity in Chinese technology community
… methods including co-occurrence analysis, TF-IDF analysis and topic models (based on LDA); this thesis also includes a field study of Chuangke, seeing how Chinese Chuangke teachers build makerspaces in their schools, engage with the Chuangke education ecosystem, nurture future makers in …
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News and financial market
… Document Frequency-Inverse Document Frequency(ADFIDF) weighting. Although occurrence of features selected by ADFIDF weighting can usually represent volatility bursts in financial market, it has been unclear whether it is also effective for market trend or trading volume. We conduct experiments …
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The effect of component recognition on flexibility and speech recognition performance in a spoken question answering system
… 46%.</p><p>Four variations of the traditional tf-idf weighting method were compared as applied to the matching of short text strings (fewer than 10 words). It was found that the general approach was successful in finding matches, and that all four variations compensated for the loss in speech …
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Integrando práticas pedagógicas efetivas para o ensino de educação financeira no ensino médio: uma análise comparativa baseada em similaridade.
… natural, especificamente através da vetorização TF-IDF e da análise de similaridade de cosseno, permitiu a categorização eficaz dos documentos, facilitando uma análise mais focada e detalhada. O uso dessa abordagem não apenas ajudou a identificar as principais tendências e padrões nas estratégias …
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A Bi-Encoder LSTM Model for Learning Unstructured Dialogs
… et al. (2015) explored learning models such as TF-IDF (Term Frequency-Inverse Document Frequency), Recurrent Neural Network (RNN) and a Dual Encoder (DE) based on Long Short Term Memory (LSTM) model suitable to learn from the Ubuntu Dialog Corpus Version 1 (UDCv1). We use this same architecture …
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An enhanced feature selection technique for classification of group based holy Quran verses
… Term Frequency-Inverse Document Frequency (TF-IDF). Meanwhile, the classification phase has involved four algorithms: Naïve Bayes (NB), k-Nearest Neighbor (k-NN), Support Vector Machine (LibSVM), and Decision Trees (J48). The experiment results were evaluated based on two established …
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Deep Assertion discovery using word embeddings
… techniques – using the numerical statistic like TF-IDF (Term Frequency-Inverse Document Frequency), using word embedding approaches like Word2Vec in Deep Learning frameworks. We have shown that the assertions discovered using our proposed framework can be effectively used for the topic-based …
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Computational criminology: at-scale quantitative analysis of the evolution of cybercrime forums
… a large corpus of literature studying these platforms, from a cross-forum ecosystem comparison to smaller qualitative analyses of specific crime types within a single forum, there has been little research into studying these over time. Using the CrimeBB dataset from the Cambridge Cybercrime …
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CSISE: cloud-based semantic image search engine
… was performed on a metadata of images using TF-IDF, and (ii) image classification was performed using a hybrid image processing model combined with Euclidean distance and SURF FLANN measurements. A Cloud-based Semantic Image Search Engine (CSISE) is also developed to search an image using the …
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