Abstract
Deep natural language processing is an algorithmic approach that enables computers to understand language using patterns, purpose, adequate experience, and a natural human data extraction context. It goes beyond a strategy for syntax and depends on a semantic strategy. Industry 5.0 democratizes the co-production of information from Big Data, building on the current symmetrical innovation concept. The Industrial Revolution 5.0 is transforming companies into working through human and computer cooperation with the massive amount of data. Industry 5.0 develops human expertise and accuracy of the computer and will be creative and satisfy consumer needs with the final product. Big data produces usable data and analyzes the best data suited for the good of the industry. The industry has no benefit from NLP converted knowledge without Big Data. Currently, users can get information from several Web sites and do not have enough time to scan all Web sites. Data is distributed with various forms of data such as education, cinema, and politics. Numerous Web sites and social media (WhatsApp, Twitter, etc.) data are distributed in the world. These different data are collected via social media and stored in one SoloDB database that allows the user to access it quickly and easily. With the authorization of the administrative process, the database information can be accessed. Deep natural language, Big Data, and artificial intelligence will be discussed, and the results will be evaluated using the Industry 5.0 private database. The combination of computer and person would make it easy to access information from the database in a customized manner.
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Devi, B.S., Muthu Selvam, M. (2022). SoloDB for Social Media’s Big Data Using Deep Natural Language with AI Applications and Industry 5.0. In: Karuppusamy, P., Perikos, I., García Márquez, F.P. (eds) Ubiquitous Intelligent Systems. Smart Innovation, Systems and Technologies, vol 243. Springer, Singapore. https://doi.org/10.1007/978-981-16-3675-2_21
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DOI: https://doi.org/10.1007/978-981-16-3675-2_21
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