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With the increasing popularity of cloud computing, more and more sensitive or private information has been outsourced onto the cloud server. For protecting data privacy, sensitive data usually has to be encrypted before outsourcing, which makes traditional search techniques based on plaintext useless. In response to the search over encrypted data, searchable encryption is a good solution in Information Security. However, most of existing searchable encryption schemes only support exact keyword search. That means they don’t support searching for different variants of the query word, which is a significant drawback and greatly affects data usability and user experience. Recently, a fuzzy keyword search scheme proposed by some researchers aims at addressing the problems of minor typos and format inconsistence but couldn’t solve the problem above. In this paper, we formalize the problem of semantic keyword-based search over encrypted cloud data while preserving privacy. Semantic keyword-based search will greatly improves the user experience by returning all the documents containing semantically close keywords related to the query word. In our solution, we use the stemming algorithm to construct stem set, which reduces the dimension of index. And the symbol-based trie is also adopted in index construction to improve the search efficiency. Through rigorous privacy analysis and experiment on real dataset, our scheme is secure and efficient.