Research Article
Fast Detection Method for Local Search Target of Community Structure Under Big Data
@INPROCEEDINGS{10.1007/978-3-030-67874-6_33, author={Wang Jing-hua and Zhou Jing-quan}, title={Fast Detection Method for Local Search Target of Community Structure Under Big Data}, proceedings={Advanced Hybrid Information Processing. 4th EAI International Conference, ADHIP 2020, Binzhou, China, September 26-27, 2020, Proceedings, Part II}, proceedings_a={ADHIP PART 2}, year={2021}, month={1}, keywords={Big data Community structure Local search Target Rapid detection method}, doi={10.1007/978-3-030-67874-6_33} }- Wang Jing-hua
Zhou Jing-quan
Year: 2021
Fast Detection Method for Local Search Target of Community Structure Under Big Data
ADHIP PART 2
Springer
DOI: 10.1007/978-3-030-67874-6_33
Abstract
The traditional detection method has the problems of complicated operation and slow search speed, which brings great impact to the efficient operation of the local search system of community structure. To this end, it studies the rapid detection method of local search target of community structure under big data. Analyze the key technologies for constructing detection methods, use quantitative algorithms to achieve rapid target location, perform resource entry on targets, and calculate data convolution kernel size. The convolution data is statistically analyzed, and the detection result is subjected to parsing and storage, thereby realizing the extraction of the target and completing the rapid detection of the local search target of the community structure. It is proved by experiments that the fast detection method of local search target of community structure has obvious advantages in search time consumption and has a good development prospect.
