10 results about "Test query" patented technology

The invention relates to the technical field of artificial intelligence, and discloses a knowledge base-based question and answer method, device and equipment and a medium, and the method comprises the following steps: obtaining document data and input query in a knowledge base, and carrying out preprocessing operation on the document data to obtain a preprocessed document set; constructing a text vectorization representation based on the preprocessed document set, generating a vectorization feature matrix, and analyzing the vectorization feature matrix through a language model to obtain a high-dimensional context representation; performing question answering on the high-dimensional context representation through an initial question answering assembly line based on the input query, outputting initial answer information, and determining an initial performance score through a test query set; and determining an optimization strategy according to the initial performance score, and optimizing the initial question and answer assembly line based on the optimization strategy to obtain a target question and answer assembly line so as to output and obtain target answer information. The method can be applied to financial science and technology or medical care service program systems, and the accuracy and efficiency of question and answer results can be improved.

Systems and methods for improving query creation and AQM are provided. A user interface is provided that allows an analyst to generate and test queries. After the analyst provides a query, one or more subsets of previous call center interactions are selected to test the provided query using methods such as a large language model or string vectorization. Once the subsets of interactions are selected, an LLM is used to evaluate the query against the subset. The evaluations may indicate interactions which were positive and which interactions were negative and may include quotes from the interactions that support the evaluations. The evaluations are presented to the analyst for review, and the analyst may revise the query in view of the evaluations. Once the analyst is satisfied with the performance of the query, the query may be used by the LLM to perform AQM for new interactions in the call center.

The invention provides a large model version recognition method and device, electronic equipment and a readable storage medium, and relates to the technical field of artificial intelligence such as large models, deep learning, natural language processing and low codes. The large model version identification method comprises the steps of obtaining a target time window according to first release time of a target version of a to-be-identified large model; obtaining a plurality of test queries according to the target time window; inserting the plurality of test queries into the service data flow of the to-be-identified large model in real time to obtain a response result output by the to-be-identified large model for each test query; obtaining an abnormal score of the to-be-identified large model according to the plurality of response results; and in response to determining that the abnormal score meets the first preset requirement, obtaining an identification result that the actual version of the to-be-identified large model is not the target version. According to the method and the device, the acquisition accuracy of test query and the identification accuracy and identification efficiency of the large model version can be improved, and the avoidance resistance during identification of the large model version is enhanced.

Embodiments of the present application provide a laboratory information management method for reducing manual workload and improving sample identification input efficiency. The method comprises: when a sample identification is input to an instrument system, receiving sample test query information sent by the instrument system, the sample test query information at least comprising the sample identification, for obtaining corresponding sample test item information; querying a hospital information system (HIS) according to the sample identification; when the sample test item information is obtained from the HIS, performing local saving on the sample identification and the corresponding sample test item information, and sending the sample test item information to the instrument system, so that the instrument system performs test and management on samples.

A method, apparatus and computer program product are provided for generating search engine input queries using point-of-interest information and permutations thereof to assess the quality of search results produced by and to improve the search engine. Methods may include: identifying a reference point-of-interest from a reference data database; extracting at least one point-of-interest attribute from the reference point-of-interest; identifying a geographic location of the reference point-of-interest; calculating a test query search center based on the geographic location of the reference point-of-interest; generating a test query based on the at least one point-of-interest attribute from the reference point-of-interest and the test query search center; querying a search engine using the test query; receiving one or more responses to the test query; analyzing the one or more responses to calculate response quality metrics; and modifying the search engine based at least in part on the metrics.

A virtual assistant platform provides a user interface for app developers to configure the enablement of domains for virtual assistants. Sets of test queries can be uploaded and statistical analyses displayed for the numbers of test queries served by each selected domain and costs for usage of each domain. Costs can vary according to complex pricing models. The user interface provides display views of tables, cost stack charts, and histograms to inform decisions that trade-off costs with benefits to the virtual assistant user experience. The platform interface shows, for individual queries, responses possible from different domains. Platform providers promote certain chosen domains.

The present application relates to remote sensing information processing technical field, for solving the problem of low algorithm accuracy of existing hyperspectral classification method, poor auxiliary training effect of source domain data set and so on, and proposes a kind of small sample hyperspectral classification method based on cross-domain spectral band alignment, comprising: S1, reading the source domain data set D source And target domain data set D target Of hyperspectral data set, calculate the aligned spectral wavelength range and the aligned band number N align ;S2, by parabolic interpolation and resampling alignment method, the spectral wavelength range and band number N align Of two data sets are unified;S3, select training sample, collect training support set and training query set to construct small sample learning task S4, train embedding network F emb Determine network model parameters;S5, collect test support set and test query set from target domain data set, determine the predicted class label of each sample using nearest neighbor algorithm, and then complete the classification of small sample hyperspectral.

The invention particularly relates to a small sample image classification method based on a Bayesian normal form, and the method comprises the steps: obtaining enough priori knowledge from an auxiliary training set based on a Bayesian thought, and then obtaining the posterior distribution of each class on the basis of a small number of support set samples through employing a Bayesian updating formula. And for the query set samples, according to the characteristics of the query set samples and the posteriori distribution of each support set category, constructing comparison distribution similarity measurement for classification. Through a Bayesian network, priori knowledge of an auxiliary training set is fully utilized by utilizing a priori updating posteriori idea, and more complete and more discriminative support set feature distribution is learned; the relation between the to-be-tested query sample and different support sets is fully considered by constructing the contrast distribution measurement, and the similarity between the to-be-tested query sample and each support set category is more effectively obtained, so that the accuracy of small sample image splitting is improved.

Systems and methods for improving query creation and AQM are provided. A user interface is provided that allows an analyst to generate and test queries. After the analyst provides a query, one or more subsets of previous call center interactions are selected to test the provided query using methods such as a large language model or string vectorization. Once the subsets of interactions are selected, an LLM is used to evaluate the query against the subset. The evaluations may indicate interactions which were positive and which interactions were negative and may include quotes from the interactions that support the evaluations. The evaluations are presented to the analyst for review, and the analyst may revise the query in view of the evaluations. Once the analyst is satisfied with the performance of the query, the query may be used by the LLM to perform AQM for new interactions in the call center.

A virtual assistant platform provides a user interface for app developers to configure the enablement of domains for virtual assistants. Sets of test queries can be uploaded and statistical analyses displayed for the numbers of test queries served by each selected domain and costs for usage of each domain. Costs can vary according to complex pricing models. The user interface provides display views of tables, cost stack charts, and histograms to inform decisions that trade-off costs with benefits to the virtual assistant user experience. The platform interface shows, for individual queries, responses possible from different domains. Platform providers promote certain chosen domains.