1266 results about "Analytic model" patented technology

A system and method for collecting, filtering, analyzing, distributing and effectively utilizing highly relevant events (such as key business events) in real time, from huge quantities of data. The present invention analyzes both historic and real-time data stemming from operational activity, by interfacing with internal data repositories (such as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM)), external data sources (such as suppliers and clients), and real time operational systems in order to create an Active Intelligence Platform. This Active Intelligence Platform is positioned as a layer between the organization's data sources and its applications, monitoring inputs and relaying only the important data items to the relevant individuals and / or systems. This allows individuals and systems to respond immediately and effectively to key events.

Methods and systems for analyzing the success of a marketing campaign by using campaign results and an original campaign database are disclosed. The method includes the steps of profiling results of the marketing campaign against a list of user defined dimensions (analytic models may be used to derive dimensions) and assigning a score to the results of the marketing campaign.

The present invention provides a system and method for information and data aggregation and analysis which provides risk managers, benefits managers, brokers, insurers and other insurance professional to have access to information resources, knowledge management tools, and powerful analytical models needed to increase their value and productivity. In accordance with one embodiment of the invention, the system and method provided is designed for information and data aggregation that allows for the compilation of data for mining and categorization by a knowledge management system, which stores all retrieved information in accordance with categories provided by a categorization engine referred to as a Taxonomy module. A contextualization module is configured to retrieve relevant information, based on various factors, including the user's profile, and the user's particular task. The system dynamically provides relevant information as the user interacts and conducts various tasks. The stored information is analyzed by a concept clustering module, so that various concepts relating to a particular topic can be uncovered and stored. In accordance with another embodiment of the invention, the system provides for various analytical tools that allow users to carry on with highly complex analysis of insurance related topics. The range of available analytical tool dynamically varies based on the user's needs and research topics. In accordance with yet another embodiment of the invention, the system provides for a unique interactive workspace that combines the features explained above in a logical manner. To this end, the system interface provides for various job templates, so as to enable the user's to carry various projects by a template driven task assignments. As the user navigates through the workspace, the range of available information to the user changes, based on the user's profile and navigation pattern.

A system and method for collecting, filtering, analyzing, distributing and effectively utilizing highly relevant events (such as key business events) in real time, from huge quantities of data. The present invention analyzes both historic and real-time data stemming from operational activity, by interfacing with internal data repositories (such as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM)), external data sources (such as suppliers and clients), and real time operational systems in order to create an Active Intelligence Platform. This Active Intelligence Platform is positioned as a layer between the organization's data sources and its applications, monitoring inputs and relaying only the important data items to the relevant individuals and / or systems. This allows individuals and systems to respond immediately and effectively to key events.

A system and method for creating virtual “flat” customer records derived from database customer data that may be used as standardized input for analytical models. A Customer Analytic Record (“CAR”) application may be created as a database object to extract, transform, and format all of the customer data needed for customer segmentation and predictive modeling. The CAR may be a set of database “views” that are defined using virtual stored queries and enabled using capabilities of a data base management system and a structured query language. The CAR is preferably a virtual “flat” record of the customer data needed for customer analytics. The customer data may be extracted by running one or more SQL queries against the database view(s). The CAR application may dynamically calculate additional variables using predetermined transformations, including custom transformations of an underlying behavior. If additional variables are created, the CAR may be modified to include the additional variables. The CAR is preferably a dynamic view of the customer record that changes whenever any update is made to the database. The definition of the CAR provides documentation of each data element available for use in models and analytics.

A computer-implemented method, a system, and a network include receiving network data from a network and non-network sourced data from one or more external sources relative to the network; performing data mining on the network data and the non-network sourced data; developing a predictive analytics model based on the data mining; and performing predictive analytics on the network data and the non-network sourced data using the predictive analytics model to detect likely future failures in the network. The network can include a Software Defined Network (SDN) operating at any of Layers 0, 1, 2 and / or 3.

A system for automated concurrency configuration of multi-threaded programs comprises one or more processors and memory coupled to the processors. The memory stores program instructions executable by the processors to implement a resource management tool. The resource management tool is configured to determine respective target values for one or more concurrency configuration parameters to be set in a deployment of an application using an analytic model and a set of performance metrics obtained from the application (e.g., values of throughput, response times, and corresponding resource utilization measurements), and to deploy the application with the concurrency configuration parameters set to the target values.

The use of visual cues associated with rendered visual items to cue a user on whether a rendered visual item has interactive capability and / or what type of interaction is possible with that visual item. The visual items may be rendered in a data driven way with each constructed using a corresponding parameterized view component. The parameter(s) are populated by data, perhaps by model variables obtained from an analytical model. The parameters then drive logic associated with the view component to thereby construct a visual item which may then be rendered. The rendering engine then renders the visual item with the visual cue. The user may then interact with the rendered visual item. Such interaction might cause some external action to occur, might change which visual items are displayed, and / or might change a value of the input parameters of one or more view components used to generate displayed visual items.

A real time decisioning service comprising a set of powerful tools accessible in ASP mode allowing an end user to create, configure, test, and deploy decision engines to automate real time decisions, comprising both expert and custom analytic models used within decision strategies, and comprising systems integration and strategy consulting is provided. An exemplary decision system is described.

An apparatus and method for monitoring a process involve development and application of a statistically qualified neuro-analytic (SQNA) model to accurately and reliably identify process change. The development of the SQNA model is accomplished in two stages: deterministic model adaption and stochastic model modification of the deterministic model adaptation. Deterministic model adaption involves formulating an analytic model of the process representing known process characteristics, augmenting the analytic model with a neural network that captures unknown process characteristics, and training the resulting neuro-analytic model by adjusting the neural network weights according to a unique scaled equation error minimization technique. Stochastic model modification involves qualifying any remaining uncertainty in the trained neuro-analytic model by formulating a likelihood function, given an error propagation equation, for computing the probability that the neuro-analytic model generates measured process output. Preferably, the developed SQNA model is validated using known sequential probability ratio tests and applied to the process as an on-line monitoring system. Illustrative of the method and apparatus, the method is applied to a peristaltic pump system.

Methods, systems, and computer program products for monitoring, aggregating, and correlating business events in real time and acting on the results with near zero latency, wherein each event is processed in the first order relative to the event density, are described herein. In an embodiment, the method operates by receiving historical values comprising keys and data fields at an analytic model. Rules associated with actions are applied to the historical values. Actions including updating data are executed pursuant to the rules, and then the method determines whether additional rules are to be applied; and performs actions associated with these additional rules until there are no remaining rules to apply. The method stores updated data in a database.

A method of informed, multi-modal travel from one or more potential routes to a defined destination includes using real-time travel-related data relative to one or more inputs of present traffic flow, emergency events, special community events, weather, historic traffic-affecting trends, and parking conditions at an informed traveler's destination; providing at least one output of using an historical database of the above real time data; generating a spatial analysis of real-time traffic flow and other traffic data; applying predictive and analytic models having rule-based constraints to selective outputs of said steps; providing guidance as to time allowed for and directions to make intermodal transfers; accounting for personal and medical information supplied by the traveler; confirming authorized users by identity confirmation and management; and providing user and management wireless access portals to the informed traveler.

Methods and systems for analyzing XML documents. The system scans an XML document, identifies different dimensions that span the XML document and detects scoping relationships amongst them. The system uses the dimensional information to create a logical hierarchical scoped dimension analysis model, maps the logical XML tree to this model, and then implements the analytical method over the logical model. The logical model allows both structural features and numeric / non-numeric data to be used for analysis. The analytical method allows users to query irregular structural properties of the XML documents using the XPath navigational API.

The method of the invention is applicable to oil production to obtain the impact of technical and economic uncertainties on the economic profitability of a reservoir and / or to optimize the position of a new well in order to meet a development strategy. The invention includes in stage 1, uncertain technical parameters having an influence on the reservoir production are selected; in stage 2, an analytic model expressing the reservoir production in the course of time is determined as a function of the parameters selected in stage 1, from production values obtained by means of a flow simulator; and in stage 3, a model expressing the economic profitability of the reservoir is determined as a function of the technical and economic parameters, from the analytic model determined in stage 2.

The invention provides a universal machine learning data analysis platform. The universal machine learning data analysis platform comprises an interface module, a data storage module, a preprocessing module, a feature extraction module, a feature conversion module, an algorithm module and a selection optimization module, wherein the feature extraction module extracts feature parameters from to-be-analyzed data according to the feature parameters set by a user; the feature conversion module is used for converting features set by the user to be in a representation form required by the user; the algorithm module comprises a plurality of algorithm models for the user to select and build, and the user builds at least one group of models; the selection optimization module selects out an optimal model and an optimal parameter from the built models and then stores the optimal model; and data generated by the modules is stored in the data storage module. According to the platform, the user can freely combine and use the modules and the algorithm models, and also can build a complex model and quickly and iteratively develop a novel analytic model, so that the working efficiency is greatly improved.

Disclosed is an improved method and system for implementing DBMS server performance optimization. According to some approaches, the method and system incorporates DBMS wizards recommendations with analytical queuing network models for purpose of evaluating different alternatives and selecting the optimum performance management solution with a set of expectations, enhancing autonomic computing by generating periodic control measures which include recommendation to add or remove indexes and materialized views, change the level of concurrency, workloads priorities, improving the balance of the resource utilization, which provides a framework for a continuous process of the workload management by means of measuring the difference between the actual results and expected, understanding the cause of the difference, finding a new corrective solution and setting new expectations.

Arrangements and methods characterize the calorimetric response of a display device. These arrangements and methods use an analytic model selected based on the type of the display device to characterize the calorimetric response of the display device. A lookup table compensates for individual characteristics of the particular display device by receiving a set of indices and providing a set of adjusted values as inputs to the analytic model.

According to an embodiment of the present invention, a method for deriving an analytic model for a session-based system is provided. The method comprises receiving, by a model generator, client-access behavior information for the session-based system, wherein the session-based system comprises a plurality of interdependent transaction types. The method further comprises deriving, by the model generator, from the received client-access behavior information, a stateless transaction-based analytic model of the session-based system, wherein the derived transaction-based analytic model models resource requirements of the session-based system for servicing a workload. According to certain embodiments, the derived transaction-based analytic model is used for performing capacity analysis of the session-based system.

A system and method that does trustworthy multi-objective structural synthesis of analog circuits, and extracts expert analog circuit knowledge from the resulting tradeoffs. The system defines a space of thousands of possible topologies via a hierarchically organized combination of designer-trusted analog building blocks, the resulting topologies are guaranteed trustworthy. The system can perform a search based on a multi-objective evolutionary algorithm that uses an age-layered population structure to balance exploration vs. exploitation, with operators that make the search space a hybrid between vector-based and tree-based representations. A scheme employing average ranking on Pareto fronts is used to handle a high number of objectives. Good initial topology sizings are quickly generated via multi-gate constraint satisfaction. To explicitly capture expert analog design knowledge, data mining is employed on the sized circuits to: automatically generate a decision tree for navigating from performance specifications to topology choice, to do global nonlinear sensitivity analysis, and to generate analytical models of performance tradeoffs.

A method for web application layer attack detection and defense based on behavior characteristic matching and analysis includes presetting a defense rule base, the defense rule base including a plurality of defense rules; acquiring a record that access request data matches the defense rule base in a web application protection system and taking the record as sample data; learning the sample data to establish an analysis model; establishing a user reputation database and setting a blacklist module in the user reputation database; learning the user's access behavior through the analysis model and updating and correcting the defense rules in the defense rule base; establishing an exception defense rule base; and setting a defense method and intercepting the user's access behavior according to the defense method. By intelligently learning the user's behavior, threat behavior can be identified and intercepted quickly to ensure the security of the web server.

Method for evaluating an underground reservoir production scheme taking account of uncertainties.Flow simulator input parameters characterizing the reservoir and the production scheme are selected. An approximate analytical model allowing the reservoir responses to be predicted is constructed. A desired degree of accuracy Dp is defined, this degree of accuracy Dp measuring the difference between the responses of the model and those of the simulator. The degree of accuracy Dp(M) of the predictions of the model is calculated. A design of experiments is constructed so as to select simulations to be performed, pertinent for adjustment of the model. The simulations selected by the design of experiments are carried out, then, for each response simulated by the simulator, the analytical model is adjusted by means of an approximation method. This operation is repeated until the desired degree of accuracy Dp is reached. Finally, the production scheme is evaluated by analyzing the reservoir responses predicted by the approximate analytical model.Application: notably to the development of petroleum reservoirs for example.

A system and associated method for continuously optimizing data archive management scheduling. A job scheduler receives, from an archive management system, inputs of task information, replica placement data, infrastructure topology data, and resource performance data. The job scheduler models a flow network that represents data content, software programs, physical devices, and communication capacity of the archive management system in various levels of vertices according to the received inputs. An optimal path in the modeled flow network is computed as an initial schedule, and the archive management system performs tasks according to the initial schedule. The operations of scheduled tasks are monitored and the job scheduler produces a new schedule based on feedbacks of the monitored operations and predefined heuristics.

In a computer system with a multi-core processor having a shared cache memory level, an operating system scheduler adjusts the CPU latency of a thread running on one of the cores to be equal to the fair CPU latency which that thread would experience when the cache memory was equally shared by adjusting the CPU time quantum of the thread. In particular, during a reconnaissance time period, the operating system scheduler gathers information regarding the threads via conventional hardware counters and uses an analytical model to estimate a fair cache miss rate that the thread would experience if the cache memory was equally shared. During a subsequent calibration period, the operating system scheduler computes the fair CPU latency using runtime statistics and the previously computed fair cache miss rate value to determine the fair CPI value.

The invention discloses a simulating design system for city expressway interchanges, comprising: data acquisition, model calibration, a data-out module, an evaluation and analysis module connecting with the model calibration module and data-out module respectively, and a data amendment module connecting between the evaluation and analysis module and the model calibration module. Meanwhile a model building and design method using the design system is disclosed too, which comprises: collecting the characteristic parameter of the traffic flow of typical expressway basic sections, interchange triage / confluence area, cutting area and various ramps; building the corresponding database and traffic capacity theoretical analysis model; demarcating and amending speed and density model with determinate service level; building traffic capacity analysis model suiting the traffic flow characteristic of the city expressway interchange. At last, the design of the lectotype of the city expressway interchanges conducted by the design model comprises analyzing and forecasting the traffic, raising a preliminary scheme, calculating the traffic capacity of the interchange, analyzing the suitability, selecting a rational strategy.

Certain example embodiments relate to using Complex Event Processing (CEP) techniques for statistical analysis of cache behavior and parameters, e.g., in connection with large, potentially heterogeneous data sets (e.g., “Big Data”). A dedicated stream mining operator registers a listener to a cache and receives notifications on cache operations. For selected element attributes, a first model estimates the probability density functions of the attribute values, delivering well-defined estimates of the attribute value distributions. A second model analyzes the time elements stay in the cache (“validity”). Validity is combined with the attribute value distribution. A meaningful analysis model (Cache Element Model) can be derived by combining additional summary statistics for the validity with the attribute value distribution, describing how long elements stay in the cache for attribute values of a specific region, and how the values are distributed. It may be used to inform administrative tasks such as, optimization of cache parameters.

Factor retrieving is a major approach for pulse wave analysis. Stiffness index and cardiac output are widely used factors for cardiac risk detection. Research has been done on clinical pulse wave data which are collected by pulse oximeter. The result shows that collected factors have a positive correlation with certain cardiac risks. Some adjustments have been applied on the algorithms that increase the significance. In addition to the factor based analysis, other signal processing techniques for pulse waveforms are included such as bispectrum estimation, Wavelet transform, and weighted dynamic time warping. Bispectrum estimation and Wavelet transform have meaningful features of pulse waveforms with some special shapes. Weighted dynamic time warping compares the similarity of waveforms. It also includes medical significance into the calculation by adjusting the weight vector. This algorithm has higher accuracy when providing more samples to compare. The factor based analysis and waveform analysis compose an analytic model which can be used for risk evaluation, classification and disease detection.

A method of informed, multi-modal travel by a user choosing from potential routes to a defined destination includes using real-time travel-related data derived from a plurality of inputs of present traffic flow, emergency and scheduled events, weather, historic traffic trends, and parking conditions at a definite final destination; providing outputs of the process; generating spatial analysis of real-time traffic flow; applying predictive and analytical models with rule-based constraints to selective outputs of these steps; and providing informed traveler user and management mobile access portals. A customer-oriented analytical system supports large-scale transportation management and provide useful information to travelers allowing them to make informed decisions regarding time, duration and mode of travel along with alternative multimodal routes. The system and method are a way of distributing travelers by time, space and mode in order to optimize travel and traffic management.

A system and method for creating virtual “flat” customer records derived from database customer data that may be used as standardized input for analytical models. A Customer Analytic Record (“CAR”) application may be created as a database object to extract, transform, and format all of the customer data needed for customer segmentation and predictive modeling. The CAR may be a set of database “views” that are defined using virtual stored queries and enabled using capabilities of a data base management system and a structured query language. The CAR is preferably a virtual “flat” record of the customer data needed for customer analytics. The customer data may be extracted by running one or more SQL queries against the database view(s). The CAR application may dynamically calculate additional variables using predetermined transformations, including custom transformations of an underlying behavior. If additional variables are created, the CAR may be modified to include the additional variables. The CAR is preferably a dynamic view of the customer record that changes whenever any update is made to the database. The definition of the CAR provides documentation of each data element available for use in models and analytics.