Research Article
Intelligent Integration of Diversified Retirement Information Based on Feature Weighting
@INPROCEEDINGS{10.1007/978-3-031-50574-4_11, author={Ye Wang and Yuliang Zhang}, title={Intelligent Integration of Diversified Retirement Information Based on Feature Weighting}, proceedings={Multimedia Technology and Enhanced Learning. 5th EAI International Conference, ICMTEL 2023, Leicester, UK, April 28-29, 2023, Proceedings, Part II}, proceedings_a={ICMTEL PART 2}, year={2024}, month={2}, keywords={Feature Weighting Diversified Information Retirement Information Intelligent Integration}, doi={10.1007/978-3-031-50574-4_11} }- Ye Wang
Yuliang Zhang
Year: 2024
Intelligent Integration of Diversified Retirement Information Based on Feature Weighting
ICMTEL PART 2
Springer
DOI: 10.1007/978-3-031-50574-4_11
Abstract
When carrying out intelligent integration of retirement information, the existing data processing and analysis architecture can no longer meet the current requirements for the storage and processing of massive text data, which reduces the efficiency and accuracy of intelligent integration of diversified retirement information. Therefore, a feature-weighted intelligent integration method of multi-element retirement information is proposed. Use the packet capture mechanism to collect diversified retirement information samples, and complete the pre-processing of initial retirement information through information filtering, normalization and other steps. Intelligent calculation and distribution of diversified retirement information weights, extraction of mutual information, information gain and other characteristics of diversified retirement information, use of feature weighting algorithm to determine the type of retirement information, and complete the intelligent integration of diversified retirement information. Through the performance test experiment, it is concluded that compared with the traditional integration method, the integrity coefficient of the retirement information integration result obtained by the optimization design method has increased by 2.4%, and the information redundancy coefficient has been effectively controlled. It is applied to the retrieval of retirement information, effectively improving the retrieval speed of information.
