Name
Abstract | ||
|---|---|---|
Keyword query interface has become a de-facto standard and such systems have been used by the community for decades. The process of selecting necessary objects for a keyword query is considered as one of the most precious query problems. In top-k query, a user specifies scoring functions and k, the number of objects to be retrieved. Based on the user's scoring function, k-objects are then selected. However, the top-k objects are valuable only for users whose scoring functions are similar. In some cases, parties may not want to disclose any information during the processing. In this paper, we propose k-object selection procedure that selects various k-objects that are preferable for all users whose scoring functions are not identical. The proposed method prevents disclosures of sensitive information. The idea of skyline and top-k query along with perturbed cipher has been used to select the k-objects securely by using MapReduce framework. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1504/IJCSE.2018.093779 | INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING |
Keywords | DocType | Volume |
skyline query, top-k query, data privacy, MapReduce, mobile phone interface | Journal | 16 |
Issue | ISSN | Citations |
4 | 1742-7185 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Asif Zaman | 1 | 6 | 5.16 |
| Md. Anisuzzaman Siddique | 2 | 30 | 8.47 |
| annisa | 3 | 4 | 2.77 |
| Yasuhiko Morimoto | 4 | 528 | 341.88 |