remission
发表于 2025-3-25 05:03:33
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跳脱衣舞的人
发表于 2025-3-25 08:13:30
Conference proceedings 2020uket, Thailand, in March 2020. .The total of 50 full papers accepted for publication in these proceedings were carefully reviewed and selected from 180 submissions. The papers are organized in the following topical sections: advanced big data, machine learning and data mining; industry applications
MAL
发表于 2025-3-25 14:41:13
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栖息地
发表于 2025-3-25 18:36:00
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Anthem
发表于 2025-3-25 21:04:50
Efficient Approaches for House Pricing Prediction by Using Hybrid Machine Learning Algorithmse property, location of the house, material used for construction, age of the property, number of bedrooms and garages and so on. This paper elaborates on the performance of Linear regression and Ridge regularization for model prediction. It also details the machine learning techniques used and its significance pertaining to the results.
MORT
发表于 2025-3-26 01:46:00
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orient
发表于 2025-3-26 06:21:40
Association Rules Extraction Method for Semantic Query Processing Over Medical Big DataFurthermore, it can provide a complete keyword library for semantic relation extraction. Experiments show that TRSC algorithm can effectively recognize the low-frequency keywords and extend medical keywords library, it accurately mined the semantic relationships.
grandiose
发表于 2025-3-26 09:10:52
Popular Disease Topics Mining Method for Online Medical Communityine the underlying disease topics in the mass medical community text data, which can discover the patients high concerned diseases and symptoms, provide the reference of pathological symptoms to doctors, and support the decision-making treatment programs.
遵循的规范
发表于 2025-3-26 16:34:52
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打火石
发表于 2025-3-26 18:48:24
Exploiting CBOW and LSTM Models to Generate Trace Representation for Process Minings and Long short-term memory, for generating the trace representation. The experimental results have achieved significant improvement, i.e., not only showing the close relationship between the activities in a trace but also helping to reduce the dimension of trace representation.