Name
Abstract | ||
|---|---|---|
In the era of information, entity information in cyberspace plays an important role in many business scenarios. Using availability as a criterion for evaluation, more value can be mined from better entity data. However, due to the existence of invalid and erroneous data, the availability of entity information and the effect of business applications is affected. AEIC, a framework to evaluate the availability of entity information in cyberspace, is proposed in this paper. To identify specific data components and provide data availability evaluation methods, AEIC proposes the algorithm for identifying the attribute missing data and improves the existing algorithm for identifying similar duplicated data as well. In the evaluation of data availability, the indicator weights are calculated using the analytic hierarchy method. Our empirical study proves that AEIC is more effective and efficient than the existing research in the specific component identification and availability evaluation of data with different business-authorized categories of entity information in cyberspace. |
Year | Venue | Field |
|---|---|---|
2018 | DSC | Data science,Data availability,Computer science,Economic indicator,Missing data,Information privacy,Hierarchy,Empirical research,Cyberspace |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinlin Wang | 1 | 2 | 2.05 |
| Hongli Zhang | 2 | 267 | 41.85 |
| Binxing Fang | 3 | 380 | 88.26 |
| Xing Wang | 4 | 1 | 1.73 |
| Yuanxin Zhang | 5 | 0 | 0.68 |