Results 11 to 20 of about 142,696 (248)
Deriving TF-IDF as a Fisher Kernel [PDF]
, 2005 The Dirichlet compound multinomial (DCM) distribution has recently been shown to be a good model for documents because it captures the phenomenon of word burstiness, unlike standard models such as the multinomial distribution. This paper investigates the DCM Fisher kernel, a function for comparing documents derived from the DCM.
Charles Elkan
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Arabic Questions Classification Using Modified TF-IDF [PDF]
IEEE Access, 2021 Classifying the cognitive levels of assessment questions according to Bloom’s taxonomy can help instructors design effective assessments that are well aligned with the intended learning outcomes.
Ali Saleh Alammary
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Analyzing Documents with TF-IDF
The Programming Historian, 2019 This lesson focuses on a foundational natural language processing and information retrieval method called Term Frequency - Inverse Document Frequency (tf-idf).
Matthew J. Lavin
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Comprehensive Comparison of TF-IDF and Word2Vec in Product Sentiment Classification Using Machine Learning Models [PDF]
Journal of Applied Informatics and ComputingSentiment analysis supports data-driven decisions by turning product reviews into reliable polarity labels. We compare four text representations, TF-IDF, TF-IDF reduced via SVD, Word2Vec (trained from scratch), and a hybrid TF-IDF(SVD-300). Word2Vec, for
Asra Gretya Sinaga +2 more
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Uzbek text summarization based on TF-IDF
CoRR, 2023 The volume of information is increasing at an incredible rate with the rapid development of the Internet and electronic information services. Due to time constraints, we don't have the opportunity to read all this information. Even the task of analyzing textual data related to one field requires a lot of work. The text summarization task helps to solve
Khabibulla Madatov +2 more
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A comparative study of keyword extraction algorithms for English texts
Journal of Intelligent Systems, 2021 This study mainly analyzed the keyword extraction of English text. First, two commonly used algorithms, the term frequency–inverse document frequency (TF–IDF) algorithm and the keyphrase extraction algorithm (KEA), were introduced.
Li Jinye
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Sentiment Analysis of Chinese Comments Based on Hybrid Vector Model [PDF]
Jisuanji gongcheng, 2020 In order to solve the problem of insufficient expression of sentiment information in the TF-IDF model,this paper proposes the Senti model to extract the sentiment information in the text,including positive/negative sentiment words,negative words ...
CHEN Xi, ZHU Xiaodong, GAO Guangkuo, XIAO Fangxiong
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Scientific Journal of Informatics, 2015 Salah satu keunggulan dari sebuah lembaga/unit pelayanan adalah seberapa cepat dan akurat dalam menangani keluhan pelanggan. Keluhan yang disampaikan pelanggan umumnya memiliki kesamaan dengan keluhan-keluhan sebelumnya, sehingga solusi dari keluhan baru
Abdul Aziz +2 more
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Mendel, 2022 Examination is one of the common ways to evaluate the students’ cognitive levels in higher education institutions. Exam questions are labeled manually by educators in accordance with Bloom’s taxonomy cognitive domain. To ease the burden of the educators,
Anbuselvan Sangodiah +5 more
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Multi-Class Text Classification on Khmer News Using Ensemble Method in Machine Learning Algorithms
Acta Informatica Pragensia, 2023 The research herein applies text classification with which to categorize Khmer news articles. News articles were collected from three online websites through web scraping and grouped into nine categories.
Raksmey Phann +2 more
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