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keyword in plaintext, which may leak privacy of users in cloud storage environment. In this paper we propose an efficient privacy preserving keyword search scheme in cloud storage, the scheme satisfies the multi-user requirement with low computational overhead and flexible key management., and it is proved to be secure and
will be able to identify concepts and relationships from the dataset based on keyword searches in their own workspace and collaborate visually with other analysts using visualization tools such as a concept map view and a timeline view. The system allows analysts to parallelize the work by dividing initial sets of
time. Comparing the 'like' query in the standard SQL in relational databases, which can not decide the similarity according users' interests when keywords appear in several different fields, a novel similarity evaluation is given in algorithm of the personalized recommendation. Using the method, a personalized digital
components, assembling programs etc., but also imports ontology repository and user interest model. In order to implement program mining, we propose a component repository model based on ontology. Meanwhile, a new and efficient search mechanism is put forward which combines the search mechanism of facet, keywords, ontology and
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.