8889 results about "Statistical analysis" patented technology

A traffic monitor provides statistics of traffic using an activity input for receiving data related to activity on a server system. Events being monitored are binned by topic or term, where the terms are associated with categories. The categories can be a hierarchy of categories and subcategories, with terms being in one or more categories. The categorized events include page views and search requests and the results might be normalized over a field of events and a result output for outputting results of the normalizer as the statistical analyses of traffic.

A method and system that dynamically ranks electronic messages based on their situational and inherent dimensions, which are judged by a set of filters. These filters evaluate the different elemental metadata constituting a message and produce a priority value based on filters relevance and importance. The system iterates through queued messages, examine the structured content for expected attributes, statistically analyze unstructured content, apply dynamically weighted rules and policies to deliver a priority ranking, and then display the message and its vital attributes in accordance with the priority ranking. The system also adaptive learns and adjusts its weighted rules and policies to permit priority ranking to change on real-time or interval-based (may be user-defined) schedule. The system includes a GUI for increasing reading and processing efficiency. The GUI performs supervised and unsupervised learning from the user's behaviors, and displays messages in accordance with their priority classification.

Methods and systems for performing single molecule amplification for detection, quantification and statistical analysis of nucleic acids are provided. Methods and systems are provided for determining and quantifying lengths of nucleic acids of interest.

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

A system and method for generating a definition for malware and/or detecting malware. is described. One exemplary embodiment includes a downloader for downloading a portion of a Web site; a parser for parsing the downloaded portion of the Web site; a statistical analysis engine for determining if the downloaded portions of the Web site should be evaluated by the active browser; an active browser for identifying changes to the known configuration of the active browser, wherein the changes are caused by the downloaded portion of the Web site; and a definition module for generating a definition for the potential malware based on the changes to the known configuration.

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

A method of managing the power up of a device that has power down state; and at least two power up states, wherein the method includes the following steps:

• • statistically analysing the power up time profile of the device;
  • determining one or more predetermined statistical indicators associated with the stored power up time profile;
  • calculating an anticipated start up time from the statistical indicators;
  • at the anticipated start up time changing the device state from the power down state to a pre-determined one of the power up states depending on the statistical indicators;
  • maintaining the device at pre-determined power up states for a predetermined duration;
  • returning the device to the power down state if there is no user interaction with the device during the predetermined duration.

The invention, referred to herein as PeaCoCk, uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior. In contrast to traditional purchase-frequency based market basket analysis techniques, such as association rules which mostly generate obvious and spurious associations, PeaCoCk employs information-theoretic notions of consistency and similarity, which allows robust statistical analysis of the true, statistically significant, and logical associations between products. Therefore, PeaCoCk lends itself to reliable, robust predictive analytics based on purchase-behavior.

A method for screening individuals at risk for prostate cancer progression is disclosed. The method is useful for evaluating cells from patients at risk for recurrence of prostate cancer following surgery for prostate cancer. Specifically, the method uses specific Markovian nuclear texture factors, alone or in combination with other biomarkers, to determine whether the cancer will progress or lose organ confinement. In addition, methods of predicting the development of fatal metastatic disease by statistical analysis of selected biomarkers is also disclosed. The invention also contemplates a method that uses a neural network to analyze and interpret cell morphology data. Utilizing Markovian factors and other biomarkers as parameters, the network is first trained with a sets of cell data from known progressors and known non-progressors. The trained network is then used to predict prostate cancer progression in patient samples.

Financial data including general ledger activity and underlying journal entries are examined to determine whether risks of material misstatement due to fraudulent financial reporting can be identified. The financial data is analyzed statistically and modeled over time, comparing actual data values with predicted data values to identify anomalies in the financial data. The anomalous financial data is then analyzed using clustering algorithms to identify common characteristics of the various transactions underlying the anomalies. The common characteristics are then compared with characteristics derived from data known to derive from fraudulent activity, and the common characteristics are reported, along with a weight or probability that the anomaly associated with the common characteristic is an identification of risks of material misstatement due to fraud. Large volumes of financial data are therefore efficiently processed to accurately identify risks of material misstatement due to fraud in connection with financial audits, or for actual detection of fraud in connection with forensic and investigative accounting activities. The analysis is enhanced by using flow analysis methods to select subsets of financial data to examine for anomalies. Flow analysis methods are also used to reveal useful business information found in money flow graphs of financial data.

A method for identifying a fraudulent account application includes receiving a new account application comprising a plurality of identity-related fields and linking the identity-related fields associated with the new account application with identity-related fields associated with a plurality of historical account applications. The links form a graphical pattern on which statistical analysis can be performed to determine the likelihood that the new account application is fraudulent. The statistical analysis can comprise comparing the graphical pattern to a known, or normal graphical pattern in order to detect differences, or anomalies occurring in the graphical pattern associated with the new account application.

The method, program and information processing system involves filtering and securing data (security sensitive words-characters-data objects) in a source document. The adaptive filter uses a compilation of additional data (typically networked) and identifies the sensitive words/objects in the compilation of additional data, retrieves contextual, semiotic and taxonomic words/objects from the additional data compilation that are related to the sensitive words/objects. A filter is compiled with the retrieved data and the filter is used to extract sensitive words/objects and the retrieved data (words/objects) from the source document to obtain extracted data and remainder data therefrom. Contextual words related to the security sensitive words/objects are obtained based upon statistical analysis of the additional data compilation. Semiotic words related to the security words are synonyms, antonyms, and pseudonyms, syntactics relative to the target words and retrieved words, and pragmatics relative to the sensitive words and retrieved words as reflected in the compilation of additional data.

A method of storing collected data on a wireless device. User interaction with a wireless device and/or the performance of the wireless device is monitored and data related thereto collected. The collected data may be structured into a tagged hierarchical structure comprising a plurality of events that are separate and independent from one another. Each event may describe a specific application with a plurality of attributes. The tagged hierarchical structure formed as a tree structure is translated into a syntax generic language. The result may be formed into a compact format using a zipped format and/or a binary-equivalent format and then stored and transmitted to a central location (e.g., a server) for statistical analysis processing. The server transforms the received data into expanded format and forms a hierarchical tree structure for each event and its attributes. The result is processed for producing a statistical analysis of the collected data.

The present invention provides methods and apparatus for selecting relating to content selection. In one aspect, the invention provides methods and apparatus for determining appropriate content based upon various other input data, particularly for individuals on whom personal data is already known. In another aspect of the invention provides method and apparatus for analyzing feedback statistics obtained from previously delivered content in order to update new content for delivery. Another aspect of the invention is combinations of content determination with the analysis of feedback statistics, preferably in real-time, to take into account not only individual preferences, but environmental and other factors. An embodiment of the present invention is directed toward personalized advertisements, with particularly preferred embodiments described that are implemented with an Internet media platform, an interactive digital television platform, as well as cross-platform implementations.

The invention discloses a cross monitoring method and a system based on voiceprint recognition and location tracking, belonging to the field of monitoring systems. The invention collects personal information and voice samples of a monitored target and constructs a vocalprint model thereof, and a wireless location communication terminal collects the location information thereof and the vocalprint information which are compared with filed information in the database; then, the human body movement track reflecting the monitored target and the complete report of a practical violation condition areoutput for management personnel to inspect and evaluate the performance of the monitored target; the management personnel can require and evaluate a statistical analysis report concerning the monitored target activity performance timelessly to observe the movement track and the state thereof or adjust the monitoring scheme thereof according to the performance. The invention realizes the remote location tracing of the monitored target, realizes non-contact biological identity recognition of the monitored target and satisfies the requirement of remote and non-contact monitoring of the monitoredtarget. The invention can be widely applied to the non-contact electronic monitoring and identity recognition field.

A method and system for using individualized customer models when operating a retail establishment is provided. The individualized customer models may be generated using statistical analysis of transaction data for the customer, thereby generating sub-models and attributes tailored to customer. The individualized customer models may be used in any aspect of a retail establishment's operations, ranging from supply chain management issues, inventory control, promotion planning (such as selecting parameters for a promotion or simulating results of a promotion), to customer interaction (such as providing a shopping list or providing individualized promotions).

A flow cytometer for detecting target particles such as microorganisms including biological cells and viruses as well as molecular species. The flow cytometer includes a detection system involving a CCD having a time delay integration capability to thereby increase the signal from the target particle and decrease the noise detected by the CCD. Calibration particles can be included in the sample stream of the flow cytometer for coordinating the readout of the CCD with the rate of flow of the sample stream to improve the detection capability of the CCD. Statistical analysis techniques can also be used to determine the rate of flow of target particles in the sample stream to thereby coordinate the readout rate of the CCD with the rate of flow of the target particles.

A system, method and computer program product are provided for detecting an unwanted message. First, an electronic mail message is received. Text in the electronic mail message is decomposed. Statistics associated with the text are gathered using a statistical analyzer. The statistics are analyzed for determining whether the electronic mail message is an unwanted message.