Utilization of text mining as a big data analysis tool for food science and nutrition

    Collection:
    Agricultural Communications Documentation Center (ACDC)
    Contributers:
    Tao, Dandan (author), Yang, Pengkun (author), and Feng, Hao (author)
    Format:
    Journal article
    Publication Date:
    2020
    Published:
    International
    Location:
    Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 166 Document Number: D11679
    Journal Title:
    Comprehensive Reviews of Food Science and Food Safety
    Journal Title Details:
    19 : 875-894
    Subject Term:
    attitudes, consumers, data analysis, data collection, databases, diet, food, food safety, information gathering, information sources, Internet, nutrition, nutrition information, online services, information technology, food industry, information retrieval, food information, social media, food supply, data mining, big data, food chain, food service, text mining, semantic web, and food fraud
    Notes:
    20 pages., Via online from the University of Illinois website., Authors' review provided an overview of the data sources, computational methods, and applications of text data in the food industry. Applications of text data analysis were illustrated with respect to food safety and food fraud surveillance, dietary pattern characterization, consumer-opinion mining, new-product development, food knowledge discovery, food supply-chain management, and online food systems.

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