Name
Title | ||
|---|---|---|
Knowledge discovery using an enhanced latent Dirichlet allocation-based clustering method for solving on-site assembly problems |
Abstract | ||
|---|---|---|
•We propose a text mining approach combining topic modeling, text clustering, and association rule identification algorithms for knowledge discovery.•We propose an enhanced latent Dirichlet allocation scheme to explore document-topic and topic-word distributions.•We introduce a refined DBSCAN method for text clustering.•The results demonstrate the capability and effectiveness of the proposed approach. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.rcim.2021.102246 | Robotics and Computer-Integrated Manufacturing |
Keywords | DocType | Volume |
Knowledge discovery,Assembly process,Latent Dirichlet allocation,Density-based spatial clustering of application with noise,Apriori algorithm | Journal | 73 |
ISSN | Citations | PageRank |
0736-5845 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weihang Ning | 1 | 0 | 0.34 |
| Jianhua Liu | 2 | 0 | 0.34 |
| Hui Xiong | 3 | 3 | 2.77 |