Titlebook: Data Management, Analytics and Innovation; Proceedings of ICDMA Neha Sharma,Amlan Chakrabarti,Jan Martinovic Conference proceedings 2021 Sp

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Uwe Hentschel,Manfred Kie?ling,Arn Hosemann mining Technology, Data extraction and Artificial Intelligence for text categorization. This paper will showcase the features of the technologies involved. There are three machine learning algorithms (SVM, Multinomial Na?ve Bayes and Logistic Regression) used in this paper for text categorization,

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https://doi.org/10.1007/978-3-663-14658-2its symptoms. Early diagnosis is the key for effective treatment of a disease and better living of the people. Providing sophisticated and accurate algorithms and techniques to overcome this issue will be revolutionary. Though hospitals in urban areas are using advanced technology for diagnosis and

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https://doi.org/10.1007/978-1-4614-4544-9be called as sentiment analysis. Sentiment analysis is basically extracting the tone or emotion of the writer, by understanding the text sequence. This way of approach is to understand the sentiment of a text considering as a boon in the customer management system and can easily be applied to the so

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Neha Sharma,Amlan Chakrabarti,Jan MartinovicPresents cutting-edge research in the fields of data management, analytics, and innovation.Gathers the outcomes of ICDMAI 2020, held in New Delhi, India.Offers a valuable reference resource for resear

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Advances in Intelligent Systems and Computinghttp://image.papertrans.cn/d/image/262878.jpg

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Automatic Standardization of Data Based on Machine Learning and Natural Language Processingnerate features for machine learning models automatically; The predictive machine learning models can be trained with the stratified random sampled data and ranked features from the transformed datasets.

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Presbyopia