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- W4385486828 abstract "Big data technology based on Internet of Things technology has made a breakthrough in recent years. Still, with the widespread application of big data technology, the system generates massive, all-encompassing, multi-source, heterogeneous data resources. The ability to organise, query and analyse data effectively is key to achieving technological advances in IoT. The challenge of fusing heterogeneous data from multiple sources due to factors such as data privacy, data security and transmission restrictions cannot be ignored. This paper performs knowledge extraction and data fusion on numerous heterogeneous data sources generated by IoT systems. Firstly, for multi-source heterogeneous data, a knowledge extraction model combining lexical attention mechanism is proposed to extract and transform features from the data; secondly, a model-integrated multi-source heterogeneous data fusion algorithm is proposed; finally, the algorithm is applied to multi-source heterogeneous data to achieve data fusion and deep mining of multi-source heterogeneous data." @default.
- W4385486828 created "2023-08-03" @default.
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- W4385486828 date "2023-01-01" @default.
- W4385486828 modified "2023-09-24" @default.
- W4385486828 title "A Novel Data Merging Intelligent Method for Whole System IoT" @default.
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- W4385486828 doi "https://doi.org/10.1007/978-981-99-4334-0_94" @default.
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