39results about How to "Guaranteed retrieval efficiency" patented technology

The present invention discloses a keyword searchable encryption method based on a Bloom filter with a storage structure, which the following steps: step 1, system parameter initialization; step 2, user secret key generation; step 3, retrieval index generation; and step 4, search token generation; step5,cloud storage server search on cryptograph key word. The present invention allows users to use trap door search linking with a key word to encrypt a document, allows data users to encrypt their data and store the data in the cloud storage server, when needed, the needed cryptograph data can be searched by a key word search token, and then is loaded and decoded. The present invention solves the problem of low retrieval efficiency of a conventional encryption method in the prior art.

The invention discloses a subtitle matching method and system based on image retrieval. By acquiring the image to be matched, the sample image and the subtitle content corresponding to the sample image, the collected sample image is used as the data for ELM self-encoding network training, and the subtitle content to be matched is The image and each sample image are respectively trained with the ELM self-encoding network to obtain a hash function, and the hash function is used to convert the binary code of the image to obtain the binary code sequence of the image to be matched and each sample image, and calculate the Chinese between the calculated images. According to the Hamming distance, similar image retrieval is carried out by the K nearest neighbor method to obtain the most similar sample image with the image to be matched, and finally the subtitle content corresponding to the most similar sample image is given to the image to be matched; The accuracy of image similarity retrieval, and the use of binary coding ensures the efficiency of retrieval and achieves the effect of fast and accurate image subtitle matching.

The invention discloses an image searching method, which comprises a training part and a searching part, wherein the training part comprises the following steps of: the extraction of characteristic points, the supplementation of the characteristic points and the determination of matching relationships, the generation of similar point set, the clustering of the characteristic point sets and the generation of characteristic vectors of each image in an image database; and the searching part comprises the following steps of: extracting the characteristic points of a picture to be retrieved and generating the characteristic point sets; calculating distances between each characteristic point descriptor vector and corresponding cluster centers, and determining a cluster where a current characteristic point belongs by using a smallest distance; calculating the frequency ni of each cluster where the characteristic points of the picture to be retrieved belong; based on the frequency ni of the clusters where the characteristic points of the picture to be retrieved belong, and the probability logarithm wi of each cluster, generating and unitizing the characteristic vector; and calculating Euler distances between the characteristic vector of the picture to be retrieved and the characteristic vectors of each image in a picture library, and selecting the image output with the smallest distance as a searching result.

The embodiment of the invention discloses a retrieval method and a retrieval device. The method in the embodiment of the present invention includes: obtaining a retrieval request, the retrieval request including retrieval characters; judging whether the retrieval request is to perform intelligent association on the retrieval characters or to perform content retrieval; when it is determined to perform intelligent association on the retrieval characters, Retrieving the search character in a specific field of the index database; when it is determined that the content search is performed on the search character, retrieving the search character in the index database.

The invention discloses a high-dimensional space hypersphere covering method for human motion capture data retrieval, which relates to the technical field of human motion capture, in particular to a method for expressing, extracting and retrieving characteristics in optical human motion capture data. The method introduces a distribution characteristic concept and a method of various motions of a human body in a high-dimensional space and comprises the following steps: extracting the main characteristics in human motion data; constructing characteristic vectors; by aiming at the characteristicvector of a retrieving condition (namely target motion to be retrieved), constructing a series of hypersphere covering area in the corresponding high-dimensional space; defining covering sequences and then evaluating the similarity of the covering sequences; and realizing the retrieval of the motion capture data. The method can effectively realize human motion capture data retrieval by a practical test and has favorable practicability and robustness.

The invention discloses a crawler network path tracing method based on object storage. The method comprises the steps that an object storage system and a log recorder are established, wherein the log recorder generates a result path log, and indexes from the source URL of a crawling result to a crawler result file on the object storage system are recorded in the result path log; when an external system needs to call the data in the database, the crawler result file on the object storage system is directly obtained through the indexes. According to the method, the object storage system is introduced so that the file reading and writing speed can be increased; the result path log is established so that the data can be retrieved in the log when the external system calls the data and does not need to be searched in the database, and accordingly the possibility of reading and writing conflicts is avoided.