110results about How to "Improve query accuracy" patented technology

The invention provides a webpage retrieval method sensitive to geographical positions, a search engine method and a search engine system. Firstly, a cloud server calculates geographical relevance of selected geographical hot spots of web pages in an off-line state and calculates scores of importance of each geographical hot spot of each web page by being combined with a network link structure obtained by a grid crawling unit, the scores are recorded in meta data of each corresponding web page as fields, and the meta data of each web page are stored in a space database of the server; when a user inquires on line, the server analyzes a geographical range of an inquire statement through natural language processing, calculates the geographical relevance of the inquire statement relative to the geographical hot spots according to the distance between the inquire statement and the geographical hot spots, calls the scores of corresponding geographical hot spots of the web pages in the space database, calculates scores of the web pages in a specific inquiry on line, sequences the results in a descending order, and outputs a retrieval result at the user side.

The invention discloses a method and a system of supervised web service finding based on attribution forecast and error correction of quality of service (QoS). The method and the system of the supervised web service finding based on the attribution forecast and the error correction of the QoS are mainly used for solving the problem of accurately effectively finding a credible web service meeting requirements of a user in an opened network environment, and therefore providing important technology support for the construction of a highly-credible service application system. On the one hand, the method and the system of the supervised web service finding based on the attribution forecast and the error correction of the QoS adopt a matrix compensation technology to carry out forecast or correction of the attribution of the QoS of the deficient or anamorphic services to enable the credible services based on the attribution of the QoS to be effectively implemented, on the other hand, prior class information of the services is introduced into the characteristic extraction stage indicated by the services to enhance distinguishing capability and query matching accuracy which are indicated by the services. Indicated by an evaluation result of a real web service data set, the method and the system of the supervised web service finding based on the attribution forecast and error correction of the QoS are not only high in efficiency and accuracy of service finding, but also simple to achieve, capable of enabling a system to be flexible, low in cost, and easy to popularize.

The invention belongs to the technical field of information data processing, and discloses an encrypted data retrieval and sharing method and system, a medium, equipment and an application. The method comprises the steps: performing system initialization; generating an encryption matrix index; generating a keyword trap door by using the paillier key pair; carrying out ciphertext search by using two ciphertext comparison algorithms in a search stage; after the intelligent vehicle obtains the query result, transmitting the attribute set of the intelligent vehicle to the authoritative platform; enabling the authoritative platform to decrypt the related key ciphertext based on the attribute set; and updating keywords or data. When retrieval or sharing is carried out, data is encrypted, college retrieval can be realized, fuzzy retrieval can be carried out on keywords with spelling errors, results are sorted according to relevancy, and accurate retrieval is realized; safe retrieval and sharing of data are achieved, and fuzzy retrieval can be conducted on keywords with spelling errors; the system can achieve efficient and encrypted retrieval, and how to achieve efficient encryption sharing.

The invention discloses a query method and device of a test case and an establishment method and device of the test case. The query method of the test case comprises the following steps: reading parameters included in the title of a first test case when the first test case is opened, wherein the parameters are the ones for querying a second test case having incidence relation with the first test case; adding the parameters to an initial query condition to generate a first query condition; querying the second test case having the incidence relation with the first test case according to the first query condition to obtain a first result set. Through the invention, the problem that the correct result set cannot be queried due to the need of manually inputting the query title in the prior art is solved to further achieve an effect of improving the query accuracy.

The invention discloses a text hash retrieval method based on deep learning. The method is characterized by comprising the following steps of: extracting a semantic code corresponding to each piece oforiginal vocabulary data in a word embedding matrix by using a bidirectional LSTM model; then, connecting a text convolutional neural network in parallel behind the bidirectional LSTM model, adding an attention mechanism, converting the output value of the second full connection layer into a corresponding hash code by using a sign function; reconstructing a category label by utilizing hash codes;and finally, searching vector data closest to the Hamming distance of the retrieval text hash code in the text library hash code, and completing the hash retrieval process of the retrieval text data.The method has the advantages that the learning ability of the hash model to the short text is high, the added attention mechanism can further improve the expression ability of the features, the classification layer reconstructs the category labels by utilizing hash codes, so that the hash model can utilize the label information more finely while learning binary codes, and the retrieval precisionis high.

A context sensing and complex semantic association based data space modeling method is provided. The invention relates to a data space modeling method. The method can overcome the following detects of the conventional methods: 1) context sensing performance is poor; 2) semantic relation expression ability is poor; and 3) semantic association inference ability is poor. The context sensing and complex semantic association based data space modeling method includes: a step 1, establishing a semi-structured graph model called as a complex semantic association network model COSAN of context sensing; a step 2, expressing an interpretative object of the context sensing according to the complex semantic association network model COSAN of context sensing; a step 3, acquiring a basic semantic association and a complex multi- semantic association of context sensing according to the interpretative object of context sensing; and a step 4, acquiring a semantic association inference rule according to the basic semantic association and the complex multi-semantic association of context sensing. The data space modeling method can be applied to the field of data space modeling.