| Presentation | 2009-01-16 Collaboratively Mining Maximal Frequent Pattern Relations without Disclosing Private Data Ryo HATAKEYAMA, Jiahong WANG, Eiichiro KODAMA, Toyoo TAKATA, |
|---|---|
| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | In the modern business world, very often two parties collaborate with each other for their mutual benefit. Accordingly, transactions are processed between them, with one party processing a part of a transaction, and the other continuing with the remainder. In addition to frequent patterns at one's own side, because of the mutual advantage it brings to the collaborators, to discover such a pattern relation between both sides becomes especially important that, a frequent pattern of one party is dependent upon, or associated with, a frequent pattern of the other party. Generally it is required that pattern relation mining should be conducted without disclosing private data to each other. And also, since any subpattern of a frequent pattern is also frequent, it is sufficient to mine only the maximal frequent patterns. We propose a privacy-preserving maximal pattern relation mining algorithm, called CMPRM. Extensive experiments were conducted; Experimental results demonstrated the effectiveness of CMPRM. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Global FP-tree / Maximal Pattern Relation Mining / Privacy-Preserving |
| Paper # | AI2008-41 |
| Date of Issue |
| Conference Information | |
| Committee | AI |
|---|---|
| Conference Date | 2009/1/9(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | |
| Vice Chair | |
| Secretary | |
| Assistant | |
| Paper Information | |
| Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
|---|---|
| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Collaboratively Mining Maximal Frequent Pattern Relations without Disclosing Private Data |
| Sub Title (in English) | |
| Keyword(1) | Global FP-tree |
| Keyword(2) | Maximal Pattern Relation Mining |
| Keyword(3) | Privacy-Preserving |
| 1st Author's Name | Ryo HATAKEYAMA |
| 1st Author's Affiliation | Graduate School of Software and Information Science, Iwate Prefectural University() |
| 2nd Author's Name | Jiahong WANG |
| 2nd Author's Affiliation | Faculty of Software and Information Science, Iwate Prefectural University |
| 3rd Author's Name | Eiichiro KODAMA |
| 3rd Author's Affiliation | Faculty of Software and Information Science, Iwate Prefectural University |
| 4th Author's Name | Toyoo TAKATA |
| 4th Author's Affiliation | Faculty of Software and Information Science, Iwate Prefectural University |
| Date | 2009-01-16 |
| Paper # | AI2008-41 |
| Volume (vol) | vol.108 |
| Number (no) | 382 |
| Page | pp.pp.- |
| #Pages | 5 |
| Date of Issue | |