309 results about "Search function" patented technology

A method may include obtaining a petrographic image. The method may further include determining various region proposals based on the petrographic image and a selective searching function. A respective region proposal among the region proposals may correspond to various pixels in the petrographic image according to a predetermined dimension. The method may further include determining color histogram data for the petrographic image. The method may further include determining input image data based on the petrographic image, the region proposals, and the color histogram data. The method may further include determining a rock object using the input image data and a machine-learning model.

The invention discloses an implementation method for generating a transformer substation BIM model by using a language based on an AI model, belongs to the technical field of BIM, and fills the blank of conversion from the language to the model: if a main transformer is located on the north side and is connected with a 110kV bus through a circuit breaker, the main transformer is directly converted into a compliant transformer BIM model; aiming at the existing family library of the transformer substation, realizing a searching function of an intelligent agent, accurately calling a searching tool according to parameters input by a user, and obtaining a corresponding equipment model file; and outputting a 3D model file, and strictly ensuring that the file format can be imported into the three-dimensional software (such as obj, fbx, glb and the like) of the Blog super-equal transformer substation for intercommunication.

An agent-based website search interface utilizes a multimodal model to enhance enterprise operations. Data agents collect and process diverse inputs, while an orchestrator manages these agents. The system leverages machine learning models to generate insights and automate decision-making processes. It includes tools for data visualization and validation, ensuring accuracy and reliability. By integrating generative AI, the interface provides advanced search functionalities, improving user experience and operational efficiency. This facilitates seamless interaction to answer context specific questions from complex data, offering a robust solution for enterprise-level search and analysis.

The present disclosure relates to systems, non-transitory computer-readable media, and methods for capturing snapshots of digital content displayed on a client device and searching through the captured content. The disclosed systems provide a search function for effectively traveling back in time to identify digital content previously displayed on a client device. The disclosed systems provide options for capturing snapshots of content displayed on a display screen, extracting data from the snapshots, and storing the snapshots for use when populating search results. The disclosed systems utilize machine learning models to extract text and / or to generate text versions of snapshots including extracted text, descriptions of images, transcripts of videos, and / or textual summaries from displayed documents or webpages. In response to a search query, the disclosed systems can produce search results that include digital videos including captured snapshots of content displayed by a client device over time.

An inverse design system combines a large language model (LLM) with a task-specific optimizer, which includes a search function, a forward model, and a comparator. The LLM adjusts parameters of the optimizer's components in response to a design scenario. Then the optimizer processes the design scenario to produce design candidates. Optionally, the LLM learns from the design candidates in an iterative process. A stochastic predictive modeling system combines an LLM with input distributions and a forward model. The LLM adjusts one or more of the input distributions and / or the forward model in response to a forecast scenario. Then the forward model processes a sampling of the input distributions to produce a forward distribution. Optionally, the LLM informs the sampling process. Optionally, the LLM learns from the forward distribution.

In various examples, systems and methods are disclosed relating to displaying images in chatbot / NPC / virtual agent / digital avatar / etc. responses. A system can identify text corresponding to an image in an electronic document and can store a representation of the text in association with an identifier of the image. The system can receive an input prompt for a machine-learning model. The system can generate a response to the input prompt using the machine-learning model. The response can include the image responsive to identifying the representation of the text using a searching function and an output of the machine-learning model.

The invention discloses a hybrid heterogeneous cloud workflow scheduling method based on reinforcement learning, and belongs to the technical field of cloud computing. The method comprises the following steps: aiming at a cloud workflow scheduling problem, by taking minimization of completion time as a target and taking cost and resources as constraints, a three-dimensional collaborative constraint model is constructed, and the cost constraints comprise server-free function budget and virtual machine budget; integrating the hyper-heuristic framework into a reinforcement learning algorithm; an improved reinforcement learning algorithm is adopted to solve the cloud workflow scheduling problem, optimal execution resources are selected, and an optimal scheduling scheme is obtained; and performing real-time scheduling according to the optimal scheduling scheme, and introducing a deviation feedback mechanism to monitor an execution error in real time. According to the method, the workflow scheduling problem is decomposed into a closed-loop optimization process of state perception and action decision, dynamic environment perception, multi-target tradeoff and online strategy optimization are deeply fused, the global search function is achieved, local optimization can be achieved, the algorithm complexity is low, and robustness is high.

Systems and methods are provided for implementing deep search functionality using large language models (“LLMs”). In various examples, a computing system uses at least one LLM to generate intents based on a user query, to generate alternative queries based on a selected or identified primary intent, and to generate a relevance score for each search result that is obtained from a search utility (e.g., an Internet search engine, a file storage search utility, an email search utility, or a document storage search utility) in response to a primary query (corresponding to the primary intent) and the generated alternative queries being entered into the search utility. The search results from the search utility are sorted based on the corresponding generated relevance scores, and the sorted search results are caused to be displayed to the user as a deep search response to the user query.

A social media platform provides a map-based graphical user interface (GUI) for accessing social media content submitted for public accessibility via the social media platform supported by the map-based GUI. The GUI includes a map providing interactive location-based searching functionality in that selection of a target location by the user in the GUI, such as by tapping or clicking at the target location, triggers a search for social media content having geo-tag data indicating geographic locations within a geographical search area centered on the target location. A search period for which content is returned is dynamically variable based on the duration for which the tap or click is held.

A computer-implemented method for computational textual search to find and display search identified information in documents. Search queries are processed over one or more documents either at a server or user device using match schemes that produce both binary (match or no match) and non-binary (i.e. multiple matching values) results and have relative fuzziness relationships. A fuzzier match scheme implies more results and fewer false negatives and a less fuzzy match scheme implies fewer results and fewer false positives. This fuzziness relationship allows, without changing a search string, for users to quickly change from a match scheme to a fuzzier or less fuzzy match scheme depending on user evaluation of results as containing too many false negatives or too many false positives—without becoming a programmer of complex search string metadata or an expert user of advanced search capabilities.

An inverse design system combines a large language model (LLM) with a task-specific optimizer, which includes a search function, a forward model, and a comparator. The LLM adjusts parameters of the optimizer's components in response to a design scenario. Then the optimizer processes the design scenario to produce design candidates. Optionally, the LLM learns from the design candidates in an iterative process. A stochastic predictive modeling system combines an LLM with input distributions and a forward model. The LLM adjusts one or more of the input distributions and / or the forward model in response to a forecast scenario. Then the forward model processes a sampling of the input distributions to produce a forward distribution. Optionally, the LLM informs the sampling process. Optionally, the LLM learns from the forward distribution.

In some aspects, search functionality is provided in an observability analysis system. In some implementations, search results are obtained from prior search queries, the search results include a subset of event data generated in a computing environment. Metadata are generated by analyzing the event data to identify a plurality of fields and values for each of the plurality of fields. A partial search query is received through a user interface at a first computer node; the partial search query represents at least a portion of a request to search the event data. Autocomplete suggestions are generated at the first computer node based on the partial search query and the metadata. Each of the autocomplete suggestions includes a suggested field selected from the plurality of fields, a suggested value selected from the values, or both. At least one of the autocomplete suggestions is displayed in the user interface.

The invention discloses a foot tub parameter intelligent adjustment method and system based on machine learning. The method comprises the steps of data collection, data screening, foot tub parameter prediction model establishment, global parameter optimization and foot tub parameter adjustment. The invention relates to the technical field of smart homes, in particular to a foot tub parameter intelligent adjusting method and system based on machine learning, according to the scheme, data screening is carried out by dividing data neighborhoods and defining data complexity and local density, and the accuracy and reliability of abnormal value recognition are improved; a model is established by designing an excitation function, a front double transformation layer, a residual adjustment layer and a loss function, so that the expression ability, prediction accuracy and prediction error control ability of the model are improved; parameters are optimized by designing a parameter search function and a search rule, and the search direction and step length are dynamically adjusted, so that the search process is more efficient, the anti-interference capability of the search process is enhanced, and local optimum can be jumped out.

The invention provides a natural scene ship target detection method and system, and the method comprises the steps: firstly obtaining a ship detection data set, a COCO data set and a plurality of to-be-detected natural scene pictures, and inputting the plurality of to-be-detected natural scene pictures into a YOLOv5x network model trained based on the ship detection data set, inputting the plurality of natural scene pictures containing the ships into a DINO target detection model trained based on a COCO data set to obtain a first target detection result of all the ships in each natural scene picture, and cutting out a cutting area containing the ships according to the first target detection result of each ship; calculating an included angle between a connecting line of the two contour points and the horizontal direction by adopting a contour searching function, a rotation matrix function and an affine transformation function, and rotating according to the calculated included angle to obtain a cutting area after ship direction correction; and finally, inputting the cutting area after ship direction correction into the trained YOLOv5nano network model for verification so as to complete ship target detection of a natural scene.

Examples of the present disclosure describe systems and methods for enterprise search that leverage periodically updated user context of an enterprise user for intent understanding and treat a search session as a dialog between the user and a digital assistant to allow multi-modal interaction. For example, a query input by the user may be received from a client application having search functionality and an integrated assistant. A current state of the user context may be leveraged to understand the query. Based on the understanding, one or more responsive entities may be retrieved from an enterprise search index as results. Based on the results, a response may be generated that includes the results and a prompt to cause the user to further refine the query and / or provide feedback. The response may be provided to the client application for output as part of a search session dialog between the user and assistant.

The invention relates to a channel state estimation method based on back scattering communication, and a noise source positioning method and system. The method comprises the following steps: identifying and extracting a single scattering path signal from various scattering paths from a radio frequency source sending a signal to a receiver receiving the signal; sampling a single scattering path signal, and constructing a discrete time function model of the single scattering path receiving signal; and solving the model to obtain the amplitude and phase of the signal, reconstructing the received signal, and analyzing the frequency domain through Fourier transform to realize channel state estimation. Performing covariance matrix characteristic decomposition on the single scattering path signal to determine a noise subspace; and constructing a spectrum peak search function, searching a spectrum peak, estimating a direction of arrival, and calculating the position of a noise source. According to the method, the interference of the multipath effect on channel estimation can be reduced by separating the single scattering signal, a more accurate channel model can be established and accurate noise source positioning can be carried out without a complex algorithm, and the communication quality of an AmBC system can be improved.

The invention discloses a content query method and device, electronic equipment and a computer readable medium. The method comprises the steps that to-be-queried content is acquired; in business data of at least one target business accessed to the search platform, business data matched with the to-be-queried content is searched based on a keyword search mode and a semantic search mode, and a first search result corresponding to the keyword search mode and a second search result corresponding to the semantic search mode are obtained; fusing the first search result and the second search result to obtain a fusion result; and obtaining a target query result corresponding to the to-be-queried content based on the fusion result. Therefore, access operations of different services can be realized through the search platform, so that the different services can use the search platform to realize a search function, and each access service can obtain the same search experience; in addition, the query result of the to-be-queried content is obtained in combination with keyword search and semantic search modes, and the search accuracy of the query result can be improved.

Systems and processes for providing and updating user interfaces for search functions are provided. An example process includes, at a computer system including a touch sensitive display and one or more input devices: receiving, via the one or more input devices, a request to display a user interface; in response to receiving the request to display the user interface, displaying, via the touch sensitive display, the user interface including an affordance including an indication of a number of pages of the user interface; and while displaying the user interface: detecting an occurrence of a predetermined condition; and in response to detecting the occurrence of the predetermined conditions, updating the affordance to include an indication of a search function.

Computerized systems and methods are described for enhancing search capabilities and user engagement within technology distribution platforms. The system integrates components including Real-Time Data Mesh, Single Pane of Glass User Interface, Advanced Analytics and Machine-Learning Module, and Relevancy Search Engine Module, Embodiments aggregate real-time data from multiple sources, standardize it for efficient processing, and utilize advanced analytics and machine learning models to optimize search results. A Relevancy Search Engine prioritizes search results based on relevancy scores using machine learning models and natural language processing. A Dynamic SKU Search Engine enables dynamic and responsive search functionalities personalized to user needs. A Personalization Engine provides personalized recommendations based on user profiles and interactions. A Real-Time Relevancy Adjustment Module ensures continuous optimization of search relevancy. Methods include initiating enhancement processes, analyzing search queries, processing data, and adjusting relevancy in real-time. Impact is measured using performance indicators.

The invention discloses a hybrid encryption method supporting access control and controllable data search, and relates to the field of secure data sharing. According to the method, a CP-ABE (Ciphertext Policy Attribute Based Encryption) technology and a symmetric searchable Encryption (SSE) technology are creatively combined, and a data authorization access function and a data controllable search function are integrated. As for data authorization access, CP-ABE is dominated, fine-grained access control is achieved by embedding attribute information, and it is ensured that only authorized users conforming to a preset strategy can decrypt data. For data controllable search, SSE is dominated, a data storage service provider is allowed to execute a search task based on keywords on the premise of not decrypting data, and expansion of fuzzy keyword search is supported in combination with a trusted execution environment technology. According to the method, the problems that user access is not limited and data sharing is easy to leak to an untrusted party are effectively solved. Through strict user right control, unauthorized access is prevented. And meanwhile, the targeted search of the shared data is realized, and bidirectional requirements are met.

The invention discloses a post recommendation method and device, equipment, a storage medium and a program product. The method comprises the following steps: in response to a client login request of a user, obtaining real-time geographic position information of a job application client; screening out at least one first-class aging recruitment enterprise of which the regional information is matched with the real-time geographic position information in the aging recruitment order metadata set which is maintained in real time; filling the description information of each first-class aging recruitment enterprise into a recommendation page, and displaying the recommendation page; and in response to a check ending request of the user for the recommended page, normally opening a conventional function interface of the job application client to provide a job application service for the user. According to the technical scheme of the embodiment of the invention, before a conventional job hunting function is provided for the user, a batch of recruitment enterprises matched with the real-time geographic position information of the user can be screened out for advanced recommendation for the user, so that the workload of brokers is greatly reduced, and meanwhile, the in-job achievement rate of members can be effectively guaranteed.

A server receives and rebroadcasts live streaming video content from a video capture device, such as a mobile phone or unmanned surveillance vehicle. The server includes a media server configured to stream selected video content to a client device, a video analysis system configured to analyze the live video content and generate object detection data, a storage system configured to store the generated object detection data and an identifier of the associated live video content, and a search engine configured to receive a text-based search request, search the object detection data stored in the storage system for relevant search results, and generate a list of live and stored video content associated with the relevant search results.

Aspects described herein may provide an interface and / or search functionality for a dealership to determine vehicles a customer is most likely to purchase. A recommender system may generate vehicle recommendations for a dealership to sell to a customer based on customer information, vehicle information, and dealership information. Machine learning may be used to generate the recommendations. The recommendations may be based on the vehicle preferences of a customer.

A method includes obtaining a table having a first descriptor that is applicable to each cell from a plurality of cells, and a plurality of second descriptors each applicable to a respective cell from the plurality of cells, executing a search function using at least the first descriptor as an input, wherein the search function identifies at least a first data set that is potentially relevant to the plurality of cells, displaying a first candidate data value for a first cell from the plurality of cells, wherein the candidate value is based on the first data set and the respective second descriptor for the first cell, and in response to selection of the first candidate data value, populating the plurality of cells with information from the first data set.

The invention provides a knowledge and text bidirectional alignment medical text representation enhancement method, which comprises the following steps of: constructing a text sequence X; constructing a medical knowledge graph subgraph Gx; embedding the entity into a lookup function; executing a text representation calculation instruction according to the text sequence X to obtain a text representation sequence Hx; the text representation sequence Hx is a sequence fused with text context and explicit entity information; executing a knowledge graph representation calculation instruction to obtain a structure perception representation sequence HE; executing a knowledge and text bidirectional attention calculation instruction according to the text representation sequence Hx and the structure perception representation sequence HE to obtain bidirectional attention weight matrixes A and B; according to the bidirectional attention weight matrix A and the bidirectional attention weight matrix B, executing an attention weighted fusion and enhancement instruction to obtain an enhanced text representation Henhanced; the technical problem of insufficient fusion of text information and external medical knowledge base information is solved.

Devices, systems, and methods for tokenizing search attributes and terms of a search query for an index-based search. A method may include receiving, by a search service of a provider network, a first search query to search a first searchable document set, the first search query including a first search term in a first language; applying a first tokenization rule to identify the first search term in the first search query; determining that the first search term is in the first language; applying a second tokenization rule to tokenize the first search term based on the first search term being in the first language; causing a launch of a search instance by a managed compute service of the provider network, the search instance to execute a search function for a keyword-based text search using the tokenized first search term.

The invention provides a search result recommendation method and equipment, which are used for improving the search performance of electronic equipment and improving the use experience of a user on a search function of the electronic equipment. According to the method, the electronic equipment detects and responds to a search instruction of a user, and a search word can be obtained; the electronic equipment can obtain at least one piece of equipment use information; based on the obtained search term and the equipment use information, the electronic equipment can provide a search result matched with the equipment use information of the electronic equipment, and the provided search result can be obtained after screening and / or sorting. Therefore, the search result provided by the electronic equipment can fit the use habit of the user or can be matched with the use state of the electronic equipment, so that the use experience of the user can be improved.

The invention provides a CT high-voltage power supply remote diagnosis data fine-grained access encryption method and system, and relates to the technical field of medical data processing. The method supports a ciphertext forward search function, so that the search token can only be used for searching the ciphertext generated before the generation time of the search token, and the problem of unauthorized search of the cloud server is effectively solved; an intersection search function of a keyword-free domain is supported, flexible multi-keyword fuzzy search is realized, and the practicability and fault tolerance of the system are improved; and an outsourcing pre-decryption function is supported, and a data user can complete correctness verification of outsourcing pre-decryption without downloading a complete partial decryption ciphertext, so that the calculation and communication overhead of the data user is effectively reduced.

The invention discloses a multi-modal file data co-processing management system, which relates to the technical field of file management and comprises a data input layer, a data storage layer, a data processing layer, a business logic layer, an application layer, an integration layer, a security monitoring layer and an infrastructure layer. The method not only supports management and processing of various data types, improves data inclusivity and processing capability, but also has real-time cooperation and version control functions, improves team cooperation efficiency, reduces data conflicts, ensures data integrity and consistency, simplifies data entry, classification, filing and retrieval processes through automatic tools and algorithms, and improves the efficiency of team cooperation. And meanwhile, an intelligent search function is provided, required data can be quickly positioned, a user can remotely access archive data from any place with network connection, the accessibility of the data is improved, the system also supports cross-department data sharing, and the circulation and collaboration of information are promoted.

The invention relates to an enterprise document management system and management method. The enterprise document management system comprises a document management module, a document retrieval module, a workflow management module, an authority management module, a user management module and a statistics and analysis module. The method can help enterprises to effectively manage and utilize the enterprise documents, and aims to provide a centralized, safe and efficient platform to help the enterprises to store, maintain and retrieve various types of documents. Through the system, an enterprise can better manage the life cycle of a document and ensure the security and reliability of the document, and meanwhile, the system aims at improving the cooperation efficiency of a team, promoting the cooperation among team members through the functions of cooperative editing, version control, workflow management and the like, and in addition, improving the efficiency of the team. The enterprise document management system is also dedicated to providing a convenient document access and search function so as to improve the working efficiency and productivity of employees.