A Novel Feature Selection Approach Based on Document Frequency of Segmented Term Frequency
IEEE Access, 2018 Feature selection is a very important process in text classification. It can effectively eliminate redundant features and retain feature words with strong class distinguishing ability.
Hongfang Zhou, Shuang Han, Yibin Liu
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Feature selection by integrating document frequency with genetic algorithm for Amharic news document classification [PDF]
PeerJ Computer Science, 2022 Text classification is the process of categorizing documents based on their content into a predefined set of categories. Text classification algorithms typically represent documents as collections of words and it deals with a large number of features ...
Demeke Endalie +2 more
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Classification of movie reviews using term frequency-inverse document frequency and optimized machine learning algorithms [PDF]
PeerJ Computer Science, 2022 The Internet Movie Database (IMDb), being one of the popular online databases for movies and personalities, provides a wide range of movie reviews from millions of users.
Muhammad Zaid Naeem +5 more
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ChatGPT versus UpToDate in Preclinical Medical Education: Cross-Sectional Analysis Using Term Frequency–Inverse Document Frequency Cosine Similarity [PDF]
JMIR Medical EducationBackgroundGenerative artificial intelligence tools such as ChatGPT are increasingly used by medical students for self-directed learning. Although these models demonstrate linguistic fluency, their reliability as supplementary resources for preclinical ...
Shankar S Thiru +6 more
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Feature Selection Based on Term Frequency Reordering of Document Level
IEEE Access, 2018 In this paper, we propose a new feature selection algorithm based on term frequency reordering of document level. In our proposed algorithm, it uses the document frequency to weigh the unbalanced factors of the data sets and considers the effect of the ...
Hongfang Zhou +3 more
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Is Document Frequency Important for PRF? [PDF]
Lecture Notes in Computer Science, 2011 We introduce in this paper a new heuristic constraint for PRF models, referred to as the Document Frequency (DF) constraint, which is validated through a series of experiments with an oracle. We then analyze, from a theoretical point of view, state-of-the-art PRF models according to their relation with this constraint.
Eric Gaussier
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ComTech, 2016 The increasing availability of online information has triggered an intensive research in the area of automatic text summarization within the Natural Language Processing (NLP).
Hans Christian +2 more
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The ineffectiveness of within-document term frequency in text classification [PDF]
Information Retrieval, 2008 For the purposes of classification it is common to represent a document as a bag of words. Such a representation consists of the individual terms making up the document together with the number of times each term appears in the document. All classification methods make use of the terms. It is common to also make use of the local term frequencies at the
W John Wilbur
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Modified term frequency-inverse document frequency based deep hybrid framework for sentiment analysis. [PDF]
Multimed Tools Appl, 2023 Dey RK, Das AK.
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An Expression Recognition Algorithm Based on Term Frequency-Inverse Document Frequency and Hybrid Loss [PDF]
Jisuanji gongcheng, 2023 Facial expressions can express people's mental activities and state of mind naturally and efficiently.They profoundly affect people's communication process.In many intelligent applications, facial expression recognition is an important basis for ...
LAN Zhengjie, WANG Lie, NIE Xiong
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