Research on Distributed Search Technology of Multiple Data Sources Intelligent Information Based on Knowledge Graph
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Research on Distributed Search Technology of Multiple Data Sources Intelligent Information Based on Knowledge Graph Jihong Li 1 & Zhiqiang Wang 1 & Yuan Wang 2 & Zhaoyun Hua 3 & Wenfeng Jing 4 Received: 13 July 2020 / Revised: 12 August 2020 / Accepted: 24 August 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020
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. Keywords Knowledge graph . Multiple data sources intelligent information . Distributed search technology . Feedback correction
1 Introduction Under the background of big data era, with the emergence of massive data and the integration and cross-application of multiple data sources, the traditional data management mode and query mode are restricted to some extent [1–3]. In recent years, knowledge graph [4] as a new knowledge representation method and data management mode, plays an important * Wenfeng Jing [email protected] Jihong Li [email protected] Zhiqiang Wang [email protected] Yuan Wang [email protected] Zhaoyun Hua [email protected] 1
State Grid Zhejiang Power Co. Ltd., Hangzhou, China
2
NARI Group Co. Ltd., Nanjing, Jiangsu, China
3
State Grid Anhui Power Co. Ltd., Langxi, Xuancheng, China
4
School of Mathematics and Statistics, Xi’an, China
role in natural language processing, question answering, information retrieval and other fields. Knowledge atlas is a structured semantic knowledge base for describing concepts and their relationships in the physical world in the form of symbols. Its basic constituent units are “entity-relationshipentity” triple, and entity and its related attribute-value pairs. Entities connect with each other through relations to form a network of knowledge structures [5]. With the publication of Google Knowledge Map, the construction and Application Research of Knowledge Map has attracted wide atten
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