Searchable encryption (SE) is one of the effective techniques for searching encrypted data without decrypting it. This technique can provide a secure indexing mechanism for encrypted data and utilize a secure trapdoor to search for the encrypted data directly, thus realizing a secure ciphertext retrieval function. Existing schemes usually build a secure index directly on the whole dataset and implement the retrieval of encrypted data by implementing a secure search algorithm on the index. However, this approach requires testing many non-relevant documents, which diminishes the query efficiency. In this paper, we adopt a clustering method to preclassify the dataset, which can filter out quite a portion of irrelevant documents, thus improving the query. Concretely, we first partition the dataset into multiple document clusters using the k-means clustering algorithm; then, we design index building and searching algorithms for these document clusters; finally, by using the asymmetric scalar-product-preserving encryption (ASPE) scheme to encrypt the indexes and queries, we propose a fast searchable symmetric encryption scheme that supports ranked search. Detailed security analysis demonstrates that the proposed scheme can guarantee the data and query security of the search process. In addition, theoretical and experimental analysis indicates that our scheme outperforms other similar schemes in terms of query efficiency.