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• W2801791504 abstract "Due to data privacy considerations, the data owners usually encrypt their documents before outsourcing to the cloud. The ability to search the encrypted documents is of great importance. Existing methods usually use the keywords to express users’ query intention, however it’s difficult for the users to construct a good query without the knowledge of document collection. This paper proposes a personalized ciphertext retrieval method based on relevance feedback, which utilizes user interaction to improve the correlation with the search results. The users only need to determine the relevance of the documents instead of constructing a good query, which can greatly improve the users query satisfaction. The selected IEEE published papers are taken as a sample of the experiment. The experimental results show that the proposed method is efficient and could raise the users’ satisfaction. Compared with MRSE-HCI method, our method could achieve higher precision rate and equally high efficiency performance." @default.
• W2801791504 created "2018-05-17" @default.
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• W2801791504 date "2018-01-01" @default.
• W2801791504 modified "2023-10-06" @default.
• W2801791504 title "A Personalized Multi-keyword Ranked Search Method Over Encrypted Cloud Data" @default.
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• W2801791504 doi "https://doi.org/10.1007/978-3-319-90775-8_6" @default.
• W2801791504 hasPublicationYear "2018" @default.
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