Abstract
| Original language | English |
|---|---|
| Place of Publication | Espoo |
| Publisher | VTT Technical Research Centre of Finland |
| Number of pages | 92 |
| ISBN (Electronic) | 978-951-38-7031-7 |
| Publication status | Published - 2007 |
| MoE publication type | C1 Separate scientific books |
Publication series
| Name | VTT Publications |
|---|---|
| Publisher | VTT |
| No. | 647 |
| ISSN (Print) | 1235-0621 |
| ISSN (Electronic) | 1455-0849 |
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Keywords
- consumer data
- privacy-preserving data mining
- ubiquitous computing
Cite this
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Consumer Data and Privacy in Ubiquitous Computing : Master's thesis. / Mutanen, Teemu.
Espoo : VTT Technical Research Centre of Finland, 2007. 92 p. (VTT Publications; No. 647).Research output: Book/Report › Book (author) › Scientific › peer-review
TY - BOOK
T1 - Consumer Data and Privacy in Ubiquitous Computing
T2 - Master's thesis
AU - Mutanen, Teemu
N1 - pro gradu Project code: 11881
PY - 2007
Y1 - 2007
N2 - The privacy-preserving perspective on data mining is relatively young area. The research done in the area is mainly theoretical. The current trend with growing amount of personalization in online services has created also applications for personalized marketing. Personalized marketing services use detailed information about the context and personal history of a customer. This needs sophisticated individual identification methods, which raise privacy concern. The novelty in privacy-preserving methods is that sensitive and distributed data could be used for data mining task and the privacy of individuals is preserved. This work has two objectives: first is to use consumer data from distributed sources and study how customer segmentation is possible while preserving the privacy. The idea is to conduct the customer segmentation in a way that the data need not leave the agent holding the data. The other objective is the value of the knowledge acquired from collectively conducted segmentation. We believe that collectively conducted segmentation produces knowledge that cannot be acquired otherwise. The results of this work show that privacypreserving customer segmentation is possible and the collectively conducted segmentation produces new knowledge.
AB - The privacy-preserving perspective on data mining is relatively young area. The research done in the area is mainly theoretical. The current trend with growing amount of personalization in online services has created also applications for personalized marketing. Personalized marketing services use detailed information about the context and personal history of a customer. This needs sophisticated individual identification methods, which raise privacy concern. The novelty in privacy-preserving methods is that sensitive and distributed data could be used for data mining task and the privacy of individuals is preserved. This work has two objectives: first is to use consumer data from distributed sources and study how customer segmentation is possible while preserving the privacy. The idea is to conduct the customer segmentation in a way that the data need not leave the agent holding the data. The other objective is the value of the knowledge acquired from collectively conducted segmentation. We believe that collectively conducted segmentation produces knowledge that cannot be acquired otherwise. The results of this work show that privacypreserving customer segmentation is possible and the collectively conducted segmentation produces new knowledge.
KW - consumer data
KW - privacy-preserving data mining
KW - ubiquitous computing
M3 - Book (author)
T3 - VTT Publications
BT - Consumer Data and Privacy in Ubiquitous Computing
PB - VTT Technical Research Centre of Finland
CY - Espoo
ER -