Results 11 to 20 of about 1,562,553 (261)
Journal of Applied Engineering and Technological Science, 2021 In the SiPaGa application, the codefication search process is still inaccurate, so OPD often make mistakes in choosing goods codes. So we need Cosine Similarity and TF-IDF methods that can improve the accuracy of the search. Cosine Similarity is a method
Sintia Sintia +2 more
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Adaptive term frequency normalization for BM25 [PDF]
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011 A key component of BM25 contributing to its success is its sub linear term frequency (TF) normalization formula. The scale and shape of this TF normalization component is controlled by a parameter k1, which is generally set to a term-independent constant.
Yuanhua Lv, ChengXiang Zhai
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GBSVM: Sentiment Classification from Unstructured Reviews Using Ensemble Classifier
Applied Sciences, 2020 User reviews on social networking platforms like Twitter, Facebook, and Google+, etc. have been gaining growing interest on account of their wide usage in sentiment analysis which serves as the feedback to both public and private companies, as well as ...
Madiha Khalid +5 more
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Primary Frequency Control Using Motor Drives for Short Term Grid Disturbances
IEEE Open Journal of Industry Applications, 2021 Industrial motor systems make up a quarter of all electric sales in the United States. Variable speed drives (VSDs) can provide energy efficiency savings to the customer by regulating motor speed based on specific and varying needs.
Taylor L. Short +6 more
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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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Empirical term weighting and expansion frequency [PDF]
Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics -, 2000 We propose an empirical method for estimating term weights directly from relevance judgments, avoiding various standard but potentially trouble-some assumptions. It is common to assume, for example, that weights vary with term frequency (tf) and inverse document frequency (idf) in a particular way, e.g., tf .idf, but the fact that there are so many ...
Kyoji Umemura, Kenneth Ward Church
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Sentiment Analysis of Tweets Using Supervised Machine Learning Techniques Based on Term Frequency [PDF]
Journal of Information Technology Management, 2021 World of technology provides everyone with a great outlet to give their opinion, using social media like Twitter and other platforms. This paper employs machine learning methods for text analysis to obtain sentiments of reviews by the people on twitter ...
Deepti Aggarwal +5 more
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Lower-bounding term frequency normalization [PDF]
Proceedings of the 20th ACM international conference on Information and knowledge management, 2011 In this paper, we reveal a common deficiency of the current retrieval models: the component of term frequency (TF) normalization by document length is not lower-bounded properly; as a result, very long documents tend to be overly penalized. In order to analytically diagnose this problem, we propose two desirable formal constraints to capture the ...
Yuanhua Lv, ChengXiang Zhai
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Вестник КазНУ. Серия математика, механика, информатика, 2018 This paper is part of the research on creating semantic analysis models in web resources for defining an extremist orientation in the text. To solve this task a model was created, which consists of five stages: identifying websites of an extremist ...
M. A. Bolatbek +2 more
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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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