Data Mining from Education-Related Search Suggested Text on the Web.
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An increasing number of industries are implementing digital technology to increase efficacy due to its accelerated development. Undoubtedly, the education sector is not an exception. In addition to conducting data mining and analysis of Internet search-recommended text for the first time, this research developed and proposed the world's first algorithm and technology to obtain such text automatically and rapidly. By performing data mining on education-related search suggestion texts on the Internet, this study aims to extract educationally beneficial information. This study collects education-related search recommendation texts from YouTube using the platform as an example. Literature review and theoretical analysis; algorithm design and optimization; system design and implementation; support for applications; construction and annotation of data sets; empirical research and experimental validation; interdisciplinary research and application are some research methods employed. These are the outcomes of this research: Valuable insights were extracted from an analysis of over 50,000 lines of collected data, including popular keywords and the emotional proclivities of individuals. Thus, supporting the instructional and decision-making practices of individuals.
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