36 results about "Internet searching" patented technology

The invention relates to the field of internet search service, and discloses a big data-based investment attraction clue analysis system, which comprises a query analysis unit, a query analysis unit, a query analysis unit, a query analysis unit and a query analysis unit, wherein the query analysis unit calls an event sequence template for defining a meta event type and a standard relative time window constraint interval; the distributed retrieval and aggregation unit is used for retrieving and aggregating meta event types to entity objects; the sequential logic verification unit is used for counting the global document frequency of the meta event, reversely mapping the global document frequency to generate a zoom coefficient, dynamically correcting a time window, and judging that only an entity object in a dynamic verification interval after correction is passed; the object sorting unit generates sorting scores according to template matching integrity, and by constructing a density and window reverse coupling mechanism, the sequential logic boundary is adaptively compressed in a high background noise environment, and the retrieval signal-to-noise ratio and the logic confidence coefficient are maintained.

The present application provides a method and system for user behavior analysis based on big data. By obtaining the query logs of target users on an Internet search service platform; extracting topic tags and long-tail query data; determining multiple behavior interest degrees based on the long-tail query data, and determining multiple query interest sub-tags based on the query interest index and all the behavior interest degrees; performing query pointing association between the query interest sub-tags and the topic tags to obtain multiple pointing association vectors, and determining behavior trend characteristics based on all the pointing association vectors; obtaining the query phrase input by the target user, performing query matching between the query phrase and the behavior trend characteristics to obtain query behavior characteristics; and uploading the query behavior characteristics to the user behavior analysis center. The above solution can accurately capture the query phrases of users based on the query behavior characteristics, and make associated classification of the search interest directions of the query phrases, so as to realize the accurate analysis of the user search behavior pattern.

The invention discloses a garbage classification method based on a GMama model, and the method comprises the steps: obtaining garbage images through a camera and Internet search, and carrying out the data enhancement preprocessing; a lightweight module GML and a core module GMC are introduced into the GMama model, and the extraction capability of local and long-range spatial dependence features is enhanced through a lightweight scanning mechanism LSM and a core scanning mechanism CSM; dynamically optimizing the class imbalance problem by adopting a mixed loss function and combining focus loss and cross entropy loss; inputting the preprocessed image data into a GMama model for training and testing to obtain an optimal model; and finally, inputting a to-be-classified image into the optimal model, and outputting a classification result. According to the GMama-based garbage automatic identification method provided by the invention, efficient and accurate garbage classification is realized through lightweight design and high accuracy, and the GMama-based garbage automatic identification method is particularly suitable for resource-constrained equipment and has a wide application prospect.

The present invention discloses a garbage classification method based on the GMamba model. The method comprises: acquiring garbage images through a camera and internet search, and performing data augmentation preprocessing; introducing a lightweight module (GML) and a core module (GMC) into the GMamba model, respectively enhancing the ability to extract local and long-range spatially dependent features through a lightweight scanning mechanism (LSM) and a core scanning mechanism (CSM); employing a hybrid loss function combining focal loss and cross-entropy loss to dynamically optimize the class imbalance problem; inputting the preprocessed image data into the GMamba model for training and testing to obtain an optimal model; finally, inputting the image to be classified into the optimal model and outputting the classification result. The proposed GMamba-based automatic garbage identification method achieves efficient and accurate garbage classification with a lightweight design and high accuracy, is particularly suitable for resource-constrained devices, and has broad application prospects.

An object of a system according to an embodiment is to enable an elderly person to answer a question by voice without performing an Internet search.SOLUTION: A system includes a speech recognition unit, a generation AI unit, an answer generation unit, and a reporting unit. The voice recognition unit recognizes a voice of a user. The generation AI unit analyzes the voice recognized by the voice recognizing unit. The answer generation unit generates an answer on the basis of the voice analyzed by the generation AI unit. The notification unit notifies the user of the answer generated by the answer generation unit.SELECTED DRAWING: Figure 1

The invention discloses a self-adaptive retrieval enhancement generation method and system based on multi-dimensional semantic routing and a medium. The method comprises the following steps: receiving a user query, identifying data dependency and cognitive complexity of the query through a semantic routing model, and carrying out bottom classification in combination with a regular matching mechanism; a dynamic routing instruction is generated according to an identification result, and corresponding processing capacity is activated in a self-adaptive mode from an intuitive generation module, a retrieval enhancement module, an algorithm thinking reasoning module and the like; wherein the retrieval enhancement module has a result correlation self-checking function and an internet search bottom-taking function, and the algorithm thinking reasoning (AoT) module adopts a context example to guide a large model to simulate an algorithm search and a backtracking path in single generation; and finally, carrying out validity detection and closed-loop repair on the answers through the quality evaluation model. The problems that a traditional RAG system is rigid in process, complex, insufficient in reasoning capacity and lack of a fault-tolerant mechanism are solved, and the resource efficiency, the logic depth and the answer robustness of the question-answering system are remarkably improved.

There is provided a computer-implemented method of stopping an internet search early, the internet search being in a class of internet searches, the method using a trained machine learning model, in which the trained machine learning model has been trained on earlier internet searches in the class, and the successive results produced by those searches, to recognize when sufficient search results have been received to make continuing searching not worthwhile, and to output whether or not to continue searching; the method including inputting the internet search into the trained machine learning model, and the search's present results, and stopping the search in response to the trained machine learning model outputting that the search should be stopped. A corresponding system configured to perform the method is also provided.

The invention discloses a big data type search system based on the 5G communication technology and a search method thereof, and relates to the technical field of internet search, the big data type search system comprises a data acquisition module, a data processing module, an analysis module and an application module, the priority of an ith query, the score of a pth query result and the response time of the query are calculated through the analysis module, and the query response time is calculated through the application module; according to the method, the query priority is dynamically adjusted through multiple dimensions such as correlation, data volume, geographic position, time delay and the like, the urgent query with high correlation is preferentially processed, the problem of inaccurate priority ranking of a traditional system is solved, the system flexibly adjusts the query sequence and the strategy to improve the efficiency, the user waiting time is shortened, and the user experience is improved. The query results are intelligently sorted according to the priorities, the click rates and the user scores, it is ensured that the most relevant results are preferentially presented, meanwhile, by analyzing the query response time and dynamically optimizing the processing flow, the response time is further shortened, and the user experience is improved.

This invention relates to the field of internet search services and discloses a big data-based investment lead analysis system, comprising: a query parsing unit that calls an event sequence template defining meta-event types and standard relative time window constraint intervals; a distributed retrieval and aggregation unit that retrieves and aggregates meta-event types to entity objects; a temporal logic verification unit that statistically analyzes the global document frequency of meta-events and generates a scaling factor through reverse mapping, dynamically corrects the time window, and determines only entity objects that pass the corrected dynamic verification interval as qualified; and an object sorting unit that generates a sorting score based on the template matching completeness. This invention constructs a reverse coupling mechanism between density and window to adaptively compress temporal logic boundaries in high background noise environments, maintaining the retrieval signal-to-noise ratio and logical confidence.

A system is provided.SOLUTION: The system includes a voice input unit for inputting a question by voice, a voice recognition unit for converting voice data into text data, a search unit for performing an Internet search based on the text data, a voice response unit for converting a search result into voice data, a voice output unit for outputting the voice data to a user, a text input unit for inputting a text question, a search unit for performing an Internet search based on the text question, a text response unit for providing a method for returning a search result of the text question to the user by text, a summary generation unit for generating a summary of a voice and text question history, and a notification unit for notifying the user of a summary generation result.SELECTED DRAWING: Figure 1

The invention relates to the technical field of internet search service and wireless mobile communication short message service, and discloses a wide-area cooperative interaction control method based on a short message bearing channel, which comprises the following steps of: identifying an aggregation keyword and an environment reference variable in a cooperative interaction demand, sending a short message search request to obtain a function feature matrix and a gradient operator coefficient; the controlled terminal analyzes the short message load extraction matrix and the coefficient, and calculates a local execution gain and a time correction factor in combination with the local feature parameter, the environment variable quantity and the timestamp deviation; according to the method, through parameterization matrix distribution, a single search response spontaneously evolves into a differentiated coordination action sequence on the terminal side, the positive correlation between system scale increase and gateway bearing pressure is eliminated, and the information bearing density in a limited channel is improved.

An object of a system according to an embodiment is to efficiently acquire the latest information by using generated AI.SOLUTION: A system includes a search keyword generation unit, a search unit, a page content acquisition unit, and an analysis unit. A retrieval keyword generation part inputs contents to be investigated to the generation AI and generates an optimum retrieval keyword for deriving the contents. The search unit performs an Internet search using the search keyword generated by the search keyword generation unit. The page content acquisition unit acquires all character strings of the page selected by the search unit. The analysis unit analyzes the character string acquired by the page content acquisition unit and extracts a content to be examined.SELECTED DRAWING: Figure 1

A system is provided.SOLUTION: A system, comprising: means for inputting a news article by a user; means for transmitting the input news article to a server; means for analyzing the news article and extracting a main keyword by the server; means for generating an Internet search query based on the extracted keyword and collecting related information; means for determining authenticity of the news based on the collected data and calculating a certainty factor; means for transmitting the determination result, the certainty factor, and ground information to a terminal; and means for displaying a result received by the terminal to the user.SELECTED DRAWING: Figure 1

A computer server system and method are disclosed for personalization and customization of search results and search result rankings, such as for Internet searching. A representative server system comprises: a network interface to receive a primary query and transmit a plurality of secondary queries and search results; a data storage device storing a vector database; and one or more processors configured to generate the secondary queries, using the primary query and using responses received to prior secondary queries; to select and concatenate responses to the secondary queries; using a vector formed from the response concatenation, to perform a vector search of the vector database and obtain associated classifications or categories; to filter and rank the associated classifications or categories to generate and output personalized search results and search result rankings comprising one or more associated classifications or categories corresponding to the primary query.

A system, method, and computer program product for implementing automated digital text optimization is provided. The method includes receiving during execution of an Internet search process, digital textual content comprising embedded words, morphemes, and phrases. A specified format for generating a summary for the digital textual content is identified and probability distribution attributes are generated with respect to target vocabulary of the digital textual content. Content of the digital textual content is replaced with replacement content and an automated digital summary of the digital textual content is generated thereby enabling optimized operational functionality of a recurrent neural network (RNN) encoder-decoder hardware device. A decoded version of the automated digital summary is presented via a specialized graphical user interface.

The present technology provides a distilled generative response engine for generating responses to Internet search queries. The present technology utilizes a language model program that is made up of a collection of conditional dependencies that branch into many different sequences of prompts that are configured to transform answers to different types of search queries. This design of the language model program facilitates rapid iteration to improve responses. The language model program is used to generate distillation data that is used to train the distilled generative response engine.

The application relates to the field of internet search services and discloses a semantic retrieval system for cultural gene indexes, which comprises a basic retrieval subsystem, a dynamic graph generation subsystem and a dynamic query arbitration subsystem. The dynamic graph generation subsystem acquires an internet text stream, determines a variant word item through co-occurrence distribution drift rate and information entropy increment, constructs a dynamic evolution graph to determine a graph mapping path, and generates a bit mask according to the graph mapping path. In the storage addressing stage, the bit mask shields a corresponding storage block in a static inverted index structure, addressing interception of a variant noise document is realized, the application realizes decoupling of a semantic evolution capture mechanism and an underlying inverted index architecture, effectively suppresses storage write amplification and retrieval load avalanche caused by sudden increase of global document frequency of the variant word item, and guarantees response stability of the retrieval system under a high concurrency environment.

A computer server system and method are disclosed for personalization and customizable filtering of network search results and search result rankings, such as for Internet searching. A representative server system comprises: a network interface to receive a query from a respondent or co-respondent; at least one data storage device storing a plurality of return queries; and one or more processors adapted to access the data storage device and using the query, to select the return queries for transmission; to search the data storage device for corresponding pluralities of responses to the return queries from other co-respondents or respondents; to pair-wise score the responses and generate pair-wise alignment scores for respondent and co-respondent combinations; to sort and rank the combinations according to the alignment scores; and to output a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings.

The invention discloses a comment word frequency statistical method and device based on Internet search and a computer storage medium. The method comprises the steps of obtaining comment data including a comment text, a reviewer identity identifier, comment release time and a comment object identifier; performing cleaning, word segmentation and intention recognition on the comment text, generating an intention containing a standardized intention category and a core keyword, and generating node vector representation fusing semantic and structural information; clustering analysis is carried out based on the embedded vector of the reviewer node, and abnormal clusters conforming to the water army behavior characteristics are identified; an identification result is fed back to a data preprocessing link, and the system identification capability is optimized; the method overcomes the rhus and superficial features of a traditional method, further provides abundant and structured input for the learning of a subsequent graph neural network, and enhances the accuracy and reliability of water army recognition.

The present technology provides a distilled generative response engine for generating responses to Internet search queries. The present technology utilizes a language model program that is made up of a collection of conditional dependencies that branch into many different sequences of prompts that are configured to transform answers to different types of search queries. This design of the language model program facilitates rapid iteration to improve responses. The language model program is used to generate distillation data that is used to train the distilled generative response engine.

A computer server system and method are disclosed for personalization and customization of search results and search result rankings, such as for Internet searching. A representative server system comprises: a network interface to receive a primary query and transmit secondary queries and search results; and one or more processors configured to generate the secondary queries; to extract or transform responses into text variables; to use trained, supervised multi-class neural networks to classify the text variables to form initial classifications or categories and combine the initial classifications or categories to form resulting classifications or categories; to filter and rank the resulting classifications or categories; and to use the filtered and ranked resulting classifications or categories to generate and output the personalized search results and search result rankings, the personalized search results and search result rankings comprising one or more associated classifications or categories corresponding to the primary query.

IT asset discovery services and external attack surface management (or EASM) services identify computers, servers, smartphones, and other devices that are exposed to the public Internet. Any device that can connect to the public Internet may be vulnerable to cybersecurity attacks. The services identify a device exposed to the public Internet by generating an asset inventory discovery graph. Graphical nodes describe asset inventory investigative records, and edges between the graphical nodes describe asset inventory investigative methods. The nodes thus capture asset investigatory details (such as website URL, IP addresses, and HTML content), and the edges capture how the asset investigatory details were discovered (such as Internet searches, DNS records, and WHOIS records). The services use the asset inventory discovery graph to identify an entity's Internet-facing assets.

The present application relates to the field of intelligent data management, and specifically to an intelligent management method and system for engineering cost data based on an Internet search service. It collects engineering project retrieval inputs input by users, and captures engineering cost project data based on an Internet search service, and then uses a large language model to perform semantic expression perfection on the engineering project retrieval input, and then sends it together with the engineering cost project data into a data processing and semantic understanding model based on artificial intelligence and natural language processing technology for processing, thereby capturing the fine-grained semantic features and retrieval demand semantic features of the engineering cost project, and using the retrieval demand semantic features as query features to perform fine-grained semantic query matching on the engineering cost project data, so as to decide whether to return the engineering cost project data based on the degree of matching between the two. In this way, the smooth progress of the engineering project and the rational allocation of resources can be ensured.

The invention relates to the technical field of nursing training, in particular to a nursing remote training platform fusing internet search and news aggregation, the platform comprises a data fusion port, a knowledge matching port and a training recommendation port, the data fusion port is used for integrating multi-source dynamic data; the knowledge matching port is used for calculating the matching degree of the student ability and the knowledge system; and the disease tracing port is used for generating a personalized learning path.

To provide an information processing system and a program which can increase the number of choices of products or services to be recommended, compared to a case of preliminarily registering products or services to be recommended.SOLUTION: Attribute information is acquired from a job executed by an image processing apparatus, joblog information including at least the attribute information is stored, recommendation information for recommending a product or a service related to the joblog information is generated from a search result of a search over the Internet on the basis of the joblog information, and the recommendation information is outputted to a user.SELECTED DRAWING: Figure 1

A computer server system and method are disclosed for personalization and customizable filtering of network search results and search result rankings, such as for Internet searching. A representative server system comprises: a network interface to receive a query from a respondent or co-respondent; at least one data storage device storing a plurality of return queries; and one or more processors adapted to access the data storage device and using the query, to select the return queries for transmission; to search the data storage device for corresponding pluralities of responses to the return queries from other co-respondents or respondents; to pair-wise score the responses and generate pair-wise alignment scores for respondent and co-respondent combinations; to sort and rank the combinations according to the alignment scores; and to output a listing of the sorted and ranked respondents or co-respondents to form the personalized network search results and search result rankings.

This application provides a data privacy protection analysis method and system based on trusted data space, belonging to the technical field of Internet search. The method first acquires search click data and dwell time data; then, after anonymizing the data, it extracts click sequences and transition probabilities, and bins the dwell time to obtain duration categories; subsequently, it generates a confusion mask using an unintentional pseudo-random function, then determines a common item set by exchanging mask fragments between data nodes, and then calculates the relevance coefficient and influence weight based on the common item set and the data fragments of dwell time distribution information using linear regression; finally, it determines the quality factor based on the influence weight pointing to the clicked item, and calculates the ranking offset by combining the adjustment direction determined by the relevance coefficient and the quality factor, ultimately using the ranking offset to adjust the item click order and generate the target search interface. This application can achieve search result ranking optimization under privacy protection.

A system is provided.SOLUTION: A system comprising: means for allowing a virtual assistant to automatically appear on a talk screen when a user inputs a specific keyword on a message app; means for allowing the virtual assistant to arrange a schedule of a participant; means for allowing the virtual assistant to hear preferences of the participant and search for a store via the Internet; and means for allowing the virtual assistant to suggest a candidate store and automatically make a reservation based on a selection made by the user.SELECTED DRAWING: Figure 1

The invention relates to a computer-implemented method for optimizing an energy supply for at least one building by means of a data processing device, wherein a customer data set is received from a customer data storage device by means of a first interface, building data sets are received by means of at least one second interface, and a co-simulation is carried out on the basis of the customer data set and the building data sets while taking into account technical and economic parameters of the energy supply for the building. The customer data set and the building data sets are used as input parameters for the co-simulation, and the result of the co-simulation is at least one energy saving data set. The building data sets are determined by means of the data processing device on the basis of the customer data set in that an internet search is automatically carried out using a scraping tool and databases with publicly accessible information are accessed. The energy saving data set is transmitted to a control device associated with the building. The invention further relates to a corresponding assembly and to a computer program.