PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation
To significantly protect the user’s privacy and prevent the user’s preference disclosure from leading to malicious entrapment, we present a combination of the recommendation algorithm and the privacy protection mechanism. In this article, we present a privacy recommendation algorithm, PrivItem2Vec,...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-12-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/15501477211061250 |
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| _version_ | 1850177703694565376 |
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| author | Zhengqiang Ge Xinyu Liu Qiang Li Yu Li Dong Guo |
| author_facet | Zhengqiang Ge Xinyu Liu Qiang Li Yu Li Dong Guo |
| author_sort | Zhengqiang Ge |
| collection | DOAJ |
| description | To significantly protect the user’s privacy and prevent the user’s preference disclosure from leading to malicious entrapment, we present a combination of the recommendation algorithm and the privacy protection mechanism. In this article, we present a privacy recommendation algorithm, PrivItem2Vec, and the concept of the recommended-internet of things, which is a privacy recommendation algorithm, consisting of user’s information, devices, and items. Recommended-internet of things uses bidirectional long short-term memory, based on item2vec, which improves algorithm time series and the recommended accuracy. In addition, we reconstructed the data set in conjunction with the Paillier algorithm. The data on the server are encrypted and embedded, which reduces the readability of the data and ensures the data’s security to a certain extent. Experiments show that our algorithm is superior to other works in terms of recommended accuracy and efficiency. |
| format | Article |
| id | doaj-art-c42b2da94e284e618c356d3620fd3f39 |
| institution | OA Journals |
| issn | 1550-1477 |
| language | English |
| publishDate | 2021-12-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-c42b2da94e284e618c356d3620fd3f392025-08-20T02:18:55ZengWileyInternational Journal of Distributed Sensor Networks1550-14772021-12-011710.1177/15501477211061250PrivItem2Vec: A privacy-preserving algorithm for top-N recommendationZhengqiang Ge0Xinyu Liu1Qiang Li2Yu Li3Dong Guo4College of Computer Science and Technology, Jilin University, Changchun, ChinaCollege of Computer Science and Technology, Jilin University, Changchun, ChinaCollege of Computer Science and Technology, Jilin University, Changchun, ChinaCollege of Computer Science and Technology, Jilin University, Changchun, ChinaKey Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun, ChinaTo significantly protect the user’s privacy and prevent the user’s preference disclosure from leading to malicious entrapment, we present a combination of the recommendation algorithm and the privacy protection mechanism. In this article, we present a privacy recommendation algorithm, PrivItem2Vec, and the concept of the recommended-internet of things, which is a privacy recommendation algorithm, consisting of user’s information, devices, and items. Recommended-internet of things uses bidirectional long short-term memory, based on item2vec, which improves algorithm time series and the recommended accuracy. In addition, we reconstructed the data set in conjunction with the Paillier algorithm. The data on the server are encrypted and embedded, which reduces the readability of the data and ensures the data’s security to a certain extent. Experiments show that our algorithm is superior to other works in terms of recommended accuracy and efficiency.https://doi.org/10.1177/15501477211061250 |
| spellingShingle | Zhengqiang Ge Xinyu Liu Qiang Li Yu Li Dong Guo PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation International Journal of Distributed Sensor Networks |
| title | PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation |
| title_full | PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation |
| title_fullStr | PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation |
| title_full_unstemmed | PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation |
| title_short | PrivItem2Vec: A privacy-preserving algorithm for top-N recommendation |
| title_sort | privitem2vec a privacy preserving algorithm for top n recommendation |
| url | https://doi.org/10.1177/15501477211061250 |
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