Research on Knowledge Discovery Based on Deep Integration of Multidimensional Data Knowledge Content and Relevance in Big Data Environment

Authors

Xiao TAN, 1.Beijing Institute of Science and Technology Information,Beijing 100044 2.Beijing Scientific and Technological Strategy Decision-making Consultant Center,Beijing 100044

Keywords

knowledge service; knowledge discovery; fusion; semantic content; multidimensional data; knowledge content

Abstract

[Purpose/significance]As a knowledge service directly involved in problem solving and decision making in the big data environment,it is necessary to effectively discover deep knowledge in multi-source heterogeneous data.Through sorting out the knowledge service environment,we can have a better understanding of the methods and technologies of knowledge discovery based on the current content and multi-dimensional association and fusion.[Method/process]Articles from the perspectives of both at home and abroad and the general situation of knowledge discovery,in the big data and the fourth driven by knowledge discovery research paradigm is facing new challenges,from multidimensional data knowledge content and associated deep fusion method,the application of related literature at home and abroad were reviewed and the content analysis and comb,summarizes the research status and development trend.[Result/conclusion]As an interdisciplinary field,knowledge discovery is an important tool for mining cross-field and providing high-quality knowledge services.The research objects are becoming more and more complex,and the research methods and technologies are becoming more and more rich.However,the integration of multi-source heterogeneous data and the interpretability based on intelligent technology still face challenges.

First Page

58

Recommended Citation

TAN, Xiao (2021) "Research on Knowledge Discovery Based on Deep Integration of Multidimensional Data Knowledge Content and Relevance in Big Data Environment," Scientific Information Research: Vol. 3: Iss. 4, Article 5.
Available at: https://eng.kjqbyj.com/journal/vol3/iss4/5

Reference

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