Collaborative Filtering Fusing Label Features Based on SDAE

Huo, Huan; Liu, Xiufeng; Zheng, Deyuan; Wu, Zhen; Yu, Shengwei; Liu, Liang

doi:10.1007/978-3-319-62701-4_17

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…Cao Bin et al proposed a study on process similarity based on flowchart structure, which takes into account the complex process structure and can be combined with the process structure for modeling [3], but it is easy to cause the loss of semantic information, which is difficult to carry out in the field of remote sensing with numerous parameter information. Due to the particularity of remote sensing process customization, the traditional recommendation system has been unable to meet the requirements, which also leads to the few recommendation methods for remote sensing process modeling at present [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

A remote sensing work-flow recommendation algorithm based on logical structure

Zuo

Liu

et al. 2023

International Conference on Signal Processing, Computer Networks, and Communications (SPCNC 2022)

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With the development of remote sensing products towards the direction of civilianization and popularization, work-flow customization plays an important role in the production of remote sensing products. The traditional customized work-flow model has large time cost, complex operation and high requirements for professional knowledge. The work-flow recommendation system can improve the construction efficiency of remote sensing work-flow to some extent and assist users to design high-quality remote sensing work-flow models. However, most of the existing remote sensing work-flow modeling methods ignore the logical structure characteristics of the work-flow, leading to large errors in the calculation results of similarity. Difficult to make work-flow recommendations effectively. Therefore, this paper proposes a customized recommendation algorithm for remote sensing work-flow based on logical structure. By focusing on logical structure, the reliability of similarity calculation between work-flow is improved, so as to find similar work-flow to help users recommend the next modeling node. Firstly, the work-flow model needs to be preprocessed: the user converts the constructed work-flow model into a process structure tree by using Petri net workflow, and uses the path table generation algorithm based on logical structure to convert the model information into data information and store it in the database for subsequent data processing; Then the flow data in the flow tree set was converted into a path table according to certain rules, and then the longest common subsequence similarity of each data in the path table was calculated to obtain the similarity calculation results based on the logical structure characteristics, the most similar work-flow in the work-flow library is found and the recommendation is made for the user. The method proposed in this paper is evaluated experimentally on the real data set, in terms of recall, precision and F1-score, which shows that the method proposed in this paper can effectively improve the recommendation efficiency and meet the actual needs of users.

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Section: Introductionmentioning

confidence: 99%