Name
Abstract | ||
|---|---|---|
A method of conflict resolution which using fuzzy partial ordering relation is proposed In order to solve the problem of data quality in industrial large data analysis and processing. There were many methods, most used to describe the similarity on behalf of its description support calculation owing to problem of small symmetry ignored the description contained in the true value of information.This paper used contains a partial order relation, to support the description based on the describes of basic attributes.Then use by these multiple attribute values such as the data source reliability and dependence and describe the accuracy after preprocessing to construct hybrid fuzzy partial order model. We make the conflict resolution problem into the evaluation model and the partial order relationship into a total order ranking quality, ranking as the true value of the optimal solution. The method is fast and reasonable and avoided the difficulty of defining the distance function by ideal solution method. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/ISCID.2017.181 | 2017 10th International Symposium on Computational Intelligence and Design (ISCID) |
Keywords | Field | DocType |
component,partial ordering relation,conflict resolution,fuzzy,truth value | Data mining,Data quality,Ranking,Pattern recognition,Computational intelligence,Computer science,Conflict resolution,Fuzzy logic,Metric (mathematics),Ideal solution,Artificial intelligence,Partially ordered set | Conference |
Volume | ISSN | ISBN |
2 | 2165-1701 | 978-1-5386-3676-3 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aizhang Guo | 1 | 1 | 1.07 |
| Kun Xue | 2 | 13 | 3.87 |
| Tao Sun | 3 | 98 | 16.37 |