Intelligent Search and Recommendation of Power Grid Based on Data Lineage

With the expansion of the power grid scale, the amount of power grid operation data is increasing rapidly. Faced with massive power grid data with complex relationships, how to judge the implicit relationship between data and quickly and accurately query the data required by users is an urgent problem to be solved. This paper proposes a set of intelligent search and personalized recommendation algorithms based on data lineage, uses power grid data to build knowledge graphs, manages data through data lineage analysis, and designs three modules: sentence intent classification, knowledge search matching, and result organization. Realize intelligent search of power grid data, and finally realize personalized recommendation for similar user groups by classifying users. According to the proposed method, this paper designs experiments to verify, and the results show that the proposed method is accurate and efficient, and can well meet the search needs of power grid users.