Abstract
The traditional information search technology performs full-text indexing on the data in the Internet, searches for information by means of keyword matching index, and returns information to the user. This retrieval method does not accurately understand the user’s needs, and returns relevant links rather than the information the user needs. The user needs to find relevant information from the linked documents. In order to improve the shortcomings of the above traditional search technology, this paper is based on the knowledge map of multi-data source intelligent information distributed search technology, through data acquisition in the Internet, complete the transformation of data to knowledge to form a knowledge network and provide information retrieval. This paper studies the construction of knowledge maps for application domain representation, proposes a semantic similarity model with constraints and implicit feedback correction mechanism, and explores the realization of intelligent information search under certain conditions. Through the analysis of prototype experimental data in the application field, the accuracy of information search based on knowledge map can reach 90%, which has strong practicability.
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This work was supported by the Science and Technology Project of State Grid Corporation of China (Project number: 5211XT180045).
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Li, J., Wang, Z., Wang, Y. et al. Research on Distributed Search Technology of Multiple Data Sources Intelligent Information Based on Knowledge Graph. J Sign Process Syst 93, 239–248 (2021). https://doi.org/10.1007/s11265-020-01592-5
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DOI: https://doi.org/10.1007/s11265-020-01592-5