71 results about "Big data" patented technology

The invention discloses a telecommunication fraud prevention system and method based on big data and machine learning. The system comprises a mobile terminal, a big data analysis terminal and a fraud interdiction governance terminal, wherein the mobile terminal is used for performing fraud detection determination on current telecommunication data according to predetermined constraint rules when receiving a short message or an incoming call message, a machine learning algorithm is adopted to detect whether the telecommunication data is a telecommunication fraud, and if the detection result is that the telecommunication data is determined as a telecommunication fraud, fraud data information is uploaded to the big data analysis terminal; the big data analysis terminal is used for performing real-time statistics on the fraud data information uploaded and reported from the mobile terminal and sending fraud early-warning information to the fraud interdiction governance terminal according to a bank card account or/and a phone number with the number of received reports exceeding a certain threshold value; and the fraud interdiction governance terminal is used for taking corresponding measures in time to interdict occurrence of a telecommunication fraud event when receiving the fraud early-warning information. The system can unite the mobile terminal, an operator, a public security institution, a bank and other institutions, quick and effective prevention can be realized, and the telecommunication fraud can be cracked down in time.

The invention provides a system suitable for mass short message data processing of a data center. The system comprises a plug-in type data adapter and a frame module, wherein the plug-in type data adapter and the frame module have the functions of data acquisition, data receiving and data import; the distributed message middleware module has the functions of data classification and data transmission; the data converter module has the functions of data conversion and data storage; a data storage module; the system comprises a relational database, a non-relational database, a cache database andan application database. And the service application and management module comprises a basic service and a service management framework. The method has the following advantages: 1, plug-and-play rapiddata acquisition capability is provided; 2, efficient transmission of mass data is provided; 3, a standardized data transfer and storage integrated processing flow is provided, and the data storage efficiency is improved; 4, providing a cold and hot double database, and providing second-level response of 1 billion-level data; and 5, providing a unified external service interface and standardizedbasic data service.

The invention provides an associated information recommendation method and device. The method comprises the steps of obtaining m first weight values corresponding to m second-level information nodes associated with a first-level information node, wherein the m first weight values are obtained through click jump behaviors of a user, the first-level information node is an information node which is used by the user at current, and the m is a positive integer; determining associated information to be recommended to the user according to the m first weight values and preset n recommended information nodes, wherein the n is a positive integer. The associated information recommendation method and device have the advantages that since the click jump behaviors of the user are referred through the m first weight values, the problem of content focusing for recommending node information to the user through the contents of information nodes, uploaders or writers of the information nodes, types of the information nodes and the like is avoided; since the m first weight values are obtained by referring to the click jump behaviors of the user, the effect of recommending associated information to users through a big data concept is realized.

The invention provides an evidence-based medical result generating method and device and relates to the field of medical treatment. According to the invention, big data analysis is performed based onpatient shared resource so as to acquire a current patient result and then big data analysis is performed based on the current patient result and a prescription shared resource so as to acquire a medical prescription result, so that medical resource data share, operation convenience, high diagnosis correction rate, low time cost and labor cost, high user experience are realized. A doctor can acquire the treatment effect of the medical prescription easily and the doctor can optimize and improve the treatment level according to the treatment effect.

The invention provides a data processing method and device based on sentiment analysis, and relates to the technical field of computers. The method comprises the following steps: obtaining an originaltext database, wherein the original text database comprises text data; obtaining a sentiment analysis dictionary; obtaining a first sentiment weight according to the sentiment analysis dictionary; obtaining an online sequence-extreme learning machine model; dynamically adjusting a prediction model according to the online sequence-extreme learning machine model, and obtaining a second sentiment weight; and determining a third sentiment weight according to the first sentiment weight and the second sentiment weight. The data processing method based on the sentiment analysis provided by the invention solves the technical problem that quick and accurate sentiment analysis cannot be carried out on a real-time network data stream in the prior art, and achieves the technical effect of realizing quasi-real time sentiment analysis and processing on massive texts on the basis of a big data platform.

The invention discloses a public sentiment network monitoring method and device of smart home care big data, and relates to the field of smart home care. The method comprises the following steps of: calculating obtained operation information which aims at the publishing contents of the same event to obtain standardized data, wherein the operation information comprises an operation information type and an information publishing platform; according to the operation information type, the information publishing platform and the publishing contents, obtaining a public sentiment monitoring index; and when the public sentiment monitoring index exceeds a preset threshold value, generating early warning information. By use of the public sentiment network monitoring method, the smart home care big data can be subjected to public sentiment network monitoring, various classes of operation behaviors of a user can be monitored, and a public sentiment monitoring result is more accurate.

The invention discloses a multi-source heterogeneous platform data processing method, which mainly comprises data acquisition, log standardization processing and data storage, and is characterized in that the log standardization processing is used for processing various different types of data to obtain a uniform format; the method specifically comprises the following steps: providing pre-processing such as asset recognition, collection, data deduplication, classification and tagging for collected assets; the collected logs and events are normalized, classified, filtered and merged in real time, and logs in a standard format are input for analysis and storage; performing asset synchronous matching on the collected vulnerabilities and configuration defects; performing threat detection and abnormal flow detection on the collected flow data, outputting analysis processing, and inputting suspicious files and data packets to a big data platform; and performing information collection, cleaning, normalizing, fusion and the like on the connected information. According to the method, management logs and alarm information with various data sources and complex formats can be processed, and normalized management is carried out, so that the data processing capability is improved.

The invention discloses an open type air quality monitoring system, relates to the technical field of air quality monitoring, adopts a movable low-cost air quality detection terminal, combines an opentype big data system architecture, perfects an existing air quality monitoring network, reduces the cost of the air quality monitoring system, and realizes data sharing to the maximum extent. A dynamic intelligent air prediction algorithm is adopted, the advantages of large air quality detection equipment and a common air quality detection terminal are fused, and real-time prediction of the air quality of a specific position is achieved; meanwhile, an automatic calibration technology based on a moving position is adopted, so that the precision of the air quality monitoring system is improved;it is achieved that the air quality of the current position is inquired in real time by ordinary residents through the Android App technology and the Web technology, the hysteresis and regional defects in air quality forecasting are overcome to a certain extent, and a new solution is provided for accurate forecasting of the air quality.

The invention discloses an industrial big data-based equipment residual life prediction method and system and a medium, and the method comprises the following steps: collecting the real-time operation data of equipment, carrying out the feature extraction and feature selection of the real-time operation data, and obtaining the data features; performing data drift detection according to the data features, and determining the health stage of the equipment; and obtaining a corresponding residual life prediction model according to the health stage, constructing a health factor according to the data features, inputting the health factor into the obtained residual life prediction model, and outputting an equipment residual life prediction result. According to the operation data generated in real time in industrial actual production, the health factor of the equipment is acquired, and the residual service life of the equipment at the current moment is predicted by using the health factor, so that the complete life cycle of the equipment can be more utilized, the service life waste and the time waste caused by sudden shutdown are reduced, the equipment health management is automatically carried out. The method can be widely applied to the field of prediction of the residual life of the equipment.

The invention provides a text classification data processing method and device, a storage medium and a program product, and relates to the field of data processing, in particular to the fields of natural language processing, big data, intelligent search, deep learning and the like. According to the specific implementation scheme, a plurality of initial label mining functions are constructed in advance, target parameters of the initial label mining functions are tested on a test set, and the label mining functions with the target parameters meeting training requirements of a text classification model are obtained and serve as final target mining functions; the target label mining function is used for generating the classification label of the initial text, a large amount of training data of the classification label with labels in a specific application scene can be obtained, a large amount of training data with accurate classification labels are provided for training of a text classification model, the cost of manual data labeling is greatly saved, and the efficiency of obtaining the training data is improved.

The invention relates to the field of big data, and provides a federated learning method, which comprises the following steps: sending a plurality of corresponding ID intersection requests to a plurality of data providers; receiving corresponding sample data returned by each data provider according to the corresponding ID intersection request to obtain a plurality of sample data, and uploading theplurality of sample data to the block chain; judging whether each piece of sample data has a corresponding federation model or not; if the corresponding federation model does not exist in the sampledata, sending the sample data to a target federation model for training; and if the corresponding federation model exists in the sample data, sending the sample data to the corresponding federation model for training. According to the invention, the precision and the business effect of the federated learning model are effectively improved.

The invention discloses a domain-specific Chinese event extraction method. The method includes: preprocessing, removing redundant tags, clauses and participles form original data information; dictionary building, namely performing artificial analysis of large-scale news corpus, summarizing domain-specific common characters and building a character dictionary; summarizing common expressions of reporting domain-specific events and building a trigger word based sentence pattern dictionary; sentence pattern matching, namely performing sentence pattern matching on a syntax tree according to the sentence pattern dictionary; event element extraction, namely performing character extraction on the syntax tree according to the character dictionary and performing time and place extraction on the syntax tree according to syntactic features of time and place elements. With the method, the difficulty of quickly acquiring Chinese news information in the big data environment is solved, users can get news events related to keywords by entering the keywords themselves through automatic processing, and great convenience is provided for information acquisition.

The invention discloses an authentication method, an authentication system, a storage medium and a big data authentication platform. The authentication method comprises the steps of: receiving an access request of a user; verifying the validity of the access request; and after the verification is passed, carrying out credit authentication on the user, and if the credit authentication is passed, allowing the user to access the big data platform. By verifying validity and creditability of the access request of the user, public opinion risk factors closely associated with an enterprise dominant are introduced in real time, and a credit limit threshold value of the enterprise dominant is dynamically adjusted, so that a timely and effective evaluation basis is provided for an evaluation subject, and the authentication method has the advantages of being real-time, efficient and reliable.

The invention discloses a credit evaluation and credit extension method based on big data. The method comprises the following steps: S1, obtaining enterprise information data; s2, establishing an enterprise credit evaluation model, calculating an enterprise credit score based on the enterprise information data, and generating an enterprise credit report; s3, the enterprise publishes financing demands, and a financial institution publishes credit product information; and S4, based on the enterprise credit score and the financing demand, matching a qualified credit product for the enterprise, and pushing the enterprise information and the enterprise credit report to a corresponding financial institution. Based on effective utilization of big data, an enterprise credit evaluation model is established, enterprise credit returns to the enterprise operation state itself, a financial institution is assisted to complete pre-loan evaluation credit granting, and small and medium-sized enterprises are helped to solve the problem of difficult financing and high financing cost.

The invention discloses a large-data-volume form packaging asynchronous submitting method, which comprises the following steps: when a user submits form data, firstly, carrying out set subpackaging onthe form data, and then, carrying out front-end compression on data which cannot be subpackaged, so that the data volume which must be submitted at one time can be reduced, and the pressure of a server is reduced; when the data is received at the background, decompressing the compressed data according to a fixed set mode, so that the pressure of a server can be avoided. Finally, the problems of data disorder and dirty reading easily generated under the condition of submitting a large-data-volume form are solved by adding a thread synchronization mode to the processing process of each function.

The invention discloses a household electricity safety monitoring system based on big data. The system comprises an equipment potential safety hazard comprehensive analysis platform, a household powerutilization potential safety hazard comprehensive analysis platform, a real-time abnormal fault comprehensive analysis platform, an intelligent power utilization security socket and an intelligent power utilization security protector. The equipment potential safety hazard comprehensive analysis platform is used for comprehensively analyzing and processing the household appliance operation condition, the household appliance operation environment and the whole-house household appliance operation condition uploaded by the intelligent power utilization security socket and the intelligent power utilization security protector. a household appliance life cycle big data table and a household line potential safety hazard level big data table are generated according to the analyzed and processed data; on the basis of an Internet of Things big data cloud platform, operation condition data of household electric equipment and lines are collected uninterruptedly around the clock, the abnormal stateof a household electric system is captured automatically, and in combination with an artificial intelligence analysis platform, household electric potential safety hazard troubleshooting and real-time processing of abnormal faults are realized.

The invention discloses an agricultural product supply and demand monitoring system based on big data, which includes a plurality of regional data acquisition systems, a master data processor, and cloud storage. Each regional data acquisition system transmits collected and sorted data to the master data processor, and the data is processed by the master data processor and then saved to the cloud storage. Each regional data acquisition system includes a logistics monitoring system, a production environment monitoring system, a regional processor, a GPRS communication module, and a power supply module which provides power for the regional processor and the GPRS communication module. The system has the advantages as follows: the accurate output of each agricultural product in each region and the quantity, unit price and logistics information of each transaction can be acquired, so that an accurate relationship between supply and demand can be provided; and every peasant household and purchaser can release supply and demand in the monitoring system and have an understanding of logistics information, and great convenience is brought to every peasant household, purchaser and logistics company.

The invention discloses a question setting method and device and a server. The question setting method comprises the steps: according to test question knowledge points and done test questions, obtaining different types of test questions through division in statistical data of historical question practice of a user; extracting a first type of test questions according to the division results of different types of test questions, and judging answering results of the first type of test questions; if the answering result is correct, judging the mastery degree of the knowledge points of the test questions by predicting scores; and if the answering result is incorrect, continuously extracting the second type of test questions with the lowest relevancy with the wrong answering test questions. Thequestion setting method solves the technical problem of poor effect of the question setting method. According to the question setting, the test question solving efficiency is improved, and the test question practice time is reduced on the premise of ensuring the correct rate. And meanwhile, big data statistical analysis is combined, so that the mastery degree of knowledge points can be accuratelypredicted. In addition, the question setting method is suitable for question setting application of the first driving test subject.

The invention discloses a method for manufacturing a standard capsule for plant seed sowing depth. The method comprises steps as follows: parameter design, product modeling, mold design, material mixing, putting of the mixture into a mold, compression molding, heating and airing, feeding of base fertilizer and seeds, capsule body sealing, pasting of two-dimensional codes, overall packaging. The seed capsule fully meets different soil depth standard sowing requirements of seeds, a wood bit substrate provides certain insulation and moisturizing effects, so that the seed budding rate and the survival rate of buds are increased, and the budding consistency is improved. Nitrogen, phosphorus and potassium fertilizer in a standard ratio in the substrate can provide the seeds with scientific nutrients, and the seed capsule can protect the seeds from being invaded by birds and other animals during the budding. Glutinous rice glue of the formed seed capsule is environment-friendly, breathable and permeable and can be degraded completely, rapidly and naturally, and all information and big data of the seeds and an internet entrance can be known in real time with the adoption of a two-dimensional code technology.

The invention discloses an energy efficiency evaluation system for medium and low voltage distribution network based on big data and GIS system, which comprises an impact analysis module connected with an energy saving and loss reduction analysis module; Energy-saving and loss-reducing analysis module. The invention comprises a line loss analysis module, an energy saving and loss reduction moduleand a comprehensive analysis module. Connected with MYSQL database module and distribution network transformation analysis module; MYSQL database module; and is respectively connected with the energy-saving and loss-reducing analysis module and the distribution network transformation analysis module. The analysis module of distribution network reconstruction displays the comprehensive informationof feeder and transformer in each area of distribution network through GIS system. It solves the technical problems that most of the distribution network energy conservation and loss reduction methodsdo not use the knowledge of distribution network optimization planning, weakens the global search ability, and makes the current state worse than some of the searched states, and ultimately can onlyobtain the approximate optimal solution, so that the search efficiency is reduced, and the optimal energy conservation and loss reduction scheme can not be obtained, and so on.

The invention relates to a big data technology, and discloses a topic classification method, which comprises the steps of obtaining a bag-of-words model corresponding to each article in an informationbase, the bag-of-words model being a subject term combination formed after stop words and part-of-speech screening, and the bag-of-words model comprising subject terms and occurrence frequencies corresponding to the subject terms; taking the bag-of-words models corresponding to the articles as topics of the articles in a one-to-one correspondence manner, and inputting the bag-of-words models intoan LDA topic model; judging whether the iterative training process of topic classification of the topics of the articles is converged or not by the LDA topic model according to a preset topic number;and if yes, obtaining classification information of topic classification corresponding to each output article when LDA topic model training converges. Bag-of-words models respectively corresponding to articles are respectively formed after stop words and part-of-speech screening and serve as feature input of the LDA topic model, interference of words without content value and appearing at high frequency is avoided, and noise influence in the topic classification process is eliminated.