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Showing 1 to 20 of 24 for “"Inverse Document Frequency"”.
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Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)
… of feature selection algorithm by utilizing 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 …
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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
… that improves on the commonly 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 …
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Educational System for Recommending Study Activities
… podobnosti dokumentů je využíváno metod Term Frequency - Inverse Document Frequency a vnoření slov.Pro používání modulu a jeho komunikaci modulu s rozhraním OU Analyse je implementováno RESTful API.
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Distributed Denial of Service Attack Detection
… concepts from information retrieval: Term Frequency (TF)-Inverse Document Frequency (IDF) and Latent Semantic Indexing (LSI). We analyzed web server log data generated in a distributed environment. Our evaluation results indicate that while all the approaches can detect various ranges of …
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News and financial market
… are based on Naive Bayes Classifier and Adjusted 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 …
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Mixed-Language Arabic- English Information Retrieval
… mixed queries are used to retrieve most relevant documents, regardless of their languages. To achieve this goal, however, it is essential firstly to suppress the impact of most problems that are caused by the mixed-language feature in both queries and documents and which result in biasing the …
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Machine learning and deep learning techniques for natural language processing with application to audio recordings
… was represented in numerical form using 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 …
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A Bi-Encoder LSTM Model for Learning Unstructured Dialogs
… 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 but on UDCv2 …
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An enhanced feature selection technique for classification of group based holy Quran verses
… classification problem is primarily applied in document labeling. However, the major setbacks with the existing feature selection techniques are high computational runtime associated with wrapper-based FS techniques and low classification accuracy performance associated with filter-based FS …
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Deep Assertion discovery using word embeddings
… 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 classification of …
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Investigating the Language of Engineering Education
… vocabulary. Subsequently, computing word frequency on engineering course material was investigated as an approach for characterizing this barrier. However, it was concluded that a more nuanced method was necessary.This research program was built on previous work in the fields of …
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Contextual lexicon-based sentiment analysis for social media.
… term-sentiment association metrics based on Term Frequency and Inverse Document Frequency that are able to outperform the state-of-the-art Point-wise Mutual Information on social media data. As distant supervision may not be readily applicable on some social media domains, we explore the …
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Ανάλυση συναισθήματος προφορικού λόγου από αθλητικές εκπομπές
… Regression, με χρήση της τεχνικής TF-IDF (Term Frequency – Inverse Document Frequency) για την αριθμητική αναπαράσταση των δεδομένων. Οι πειραματικές διαδικασίες επικεντρώθηκαν στην αξιολόγηση της απόδοσης των μοντέλων ως προς την ακρίβεια και την ικανότητά τους να διαχειριστούν την …
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Performance analysis of text classification algorithms for PubMed articles
… of the study text was tokenised using 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 …
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Enhancing E-commerce Dataset recommendations using BERT and Named Entity Recognition
… contextual information and applies Term Frequency-Inverse Document Frequency (TF-IDF) alongside BERT embeddings to capture both keyword relevance and semantic context. This approach enhances recommendation precision, making EDMRec especially suitable for complex e-commerce queries. …
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Integration of heterogeneous data types using self organizing maps
… data sizes and the unavailability of schema documentation; therefore, an automated tool would be definitely more suitable. Automatically detecting similar entities based on the content is challenging due to three factors. First, because the amount of records is voluminous, it is difficult to …
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Dynamic Model Generation and Semantic Search for Open Source Projects using Big Data Analytics
… analyzed for feature extraction using Term Frequency Inverse Document Frequency (TF-IDF), synonym detection using Word2Vec [3] and component detection using Machine Learning dynamically. The dependency information extracted from the call graph is then used for identifying the connectors …
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Natural Language Processing methods for short informal text
… was inspired by the relation between the word's frequency and the context words frequencies (words surrounding the selected word) over time. This relation had been translated to co-occurrence patterns and stored as word embeddings after being transformed into feature space. The features had been …
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NLP in Engineering Education - Demonstrating the use of Natural Language Processing Techniques for Use in Engineering Education Classrooms and Research
… such as Part-of-Speech tagging and tf-idf (text frequency-inverse document frequency) that were found (through my systematic review) to be used by researchers, to (a) develop an automated classification system for student responses to gauge their metacognitive levels and (b) conduct an …
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Arabic Language Processing for Text Classification. Contributions to Arabic Root Extraction Techniques, Building An Arabic Corpus, and to Arabic Text Classification Techniques.
… finally proposes and implements a variant term frequency inverse document frequency weighting method, and investigates the effect of using different choices of features in document representation on single-label text classification performance (words, stems or roots as well as including to these …
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