241 results about "Confidence factor" patented technology

Here, we introduce Z-webs, including Z-factors and Z-nodes, for the understanding of relationships between objects, subjects, abstract ideas, concepts, or the like, including face, car, images, people, emotions, mood, text, natural language, voice, music, video, locations, formulas, facts, historical data, landmarks, personalities, ownership, family, friends, love, happiness, social behavior, voting behavior, and the like, to be used for many applications in our life, including on the search engine, analytics, Big Data processing, natural language processing, economy forecasting, face recognition, dealing with reliability and certainty, medical diagnosis, pattern recognition, object recognition, biometrics, security analysis, risk analysis, fraud detection, satellite image analysis, machine generated data analysis, machine learning, training samples, extracting data or patterns (from the video, images, and the like), editing video or images, and the like. Z-factors include reliability factor, confidence factor, expertise factor, bias factor, and the like, which is associated with each Z-node in the Z-web.

The invention relates to a system and method for processing natural language text utilizing disambiguation components to identify a disambiguated sense for the text. For the method, it comprises applying a selection of the components to the text to identify a local disambiguated sense for the text. Each component provides a local disambiguated sense of the text with a confidence score and a probability score. The disambiguated sense is determined utilizing a selection of local disambiguated senses. The invention also relates to a system and method for generating sense-tagged text. For the method, it comprises steps of: disambiguating a quantity of documents utilizing a disambiguation component; generating a confidence score and a probability score for a sense identified for a word provided by the component; if the confidence score for the sense for the word is below a set threshold, the sense is ignored; and if the confidence score for the sense for the word is above the set threshold, the sense is added to the sense-tagged text.

A computer-implemented method for targeting marketing content to an online user, includes the steps of collecting data describing the user in a user profile, comparing the user profile with a target profile and presenting the user with content based on the comparison. The user profile includes a photographic likeness of the user, as well as information derived from the user's photographic likeness. Certain content may be dynamically created for the user based on the user profile and may include the photographic likeness of the user, which may be altered to incorporate a portion of the content into the photographic likeness. In this manner, personalized advertisements for cosmetics, jewelry, clothing and other items may be created. The user profile also includes data describing the user's browsing habits and responses to context-specific survey questions. In one embodiment, metrics are assigned to the user profile data, and a data index identifying the user's preferences and purchasing habits is calculated for the user based on the assigned metrics. Each metric may also have an associated confidence factor, which causes the metric value to decay over time.

If some aspect of serving or scoring an ad is subject to a performance (e.g., click-through rate, etc.) threshold, such a threshold may be adjusted using a confidence factor of the ad targeting used. For example, ads served pursuant to a more relaxed notion of match might have to meet a higher performance threshold (e.g., than the threshold applied to ads served pursuant to a stricter notion of match). Alternatively, or in addition, ads served pursuant to a stricter notion of match might be subject to a lower performance threshold (e.g., than the threshold applied to ads served pursuant to a more relaxed notion of match. Thus, in general, a performance threshold could increase as match confidence decreases, and / or a performance threshold could decrease as match confidence increases.

An electrically variable transmission has a pair of clutches and a first mode when the first clutch is applied and the second clutch released, a second mode when the second clutch is applied and the first clutch released, and a fixed-ratio mode when both clutches are applied. Upshifts and downshifts out of fixed-ratio are accomplished in accordance with a control based upon shift confidence factors determined in accordance with proportional and derivative input speed error quantities. Additional authority limits are placed upon the shift confidence factors in accordance with output speed derivative quantities. Additional override downshift control is provided in accordance with additional input speed condition determinations.

A system and method for collecting and correlating information about development of a computer software, including software tools reports. The system and method provides overview of entire software development lifecycle, provides decision support engine for project management, allows estimation of project timelines based upon empirical data, allows evaluation of project quality based upon empirical data, and correlates information from previous projects to estimate progress of current project (confidence factors). The system and method for collecting and correlating information about development of a computer software include collecting data from a plurality of software tools during each point in lifecycle of the computer software; storing the collected data in a database; and correlating the stored collected data to monitor the development of the computer software.

A data processing apparatus comprising a sensor and a context engine module. The sensor is configured to generate a sensor output signal representative of a value for one or more context aspects of the data processing apparatus and a confidence factor associated with each of the values for the one or more context aspects. The context engine module is configured to process the sensor output signal to generate and make available a final value for one or more context aspects of the data processing apparatus.

Here, we introduce Z-webs, including Z-factors and Z-nodes, for the understanding of relationships between objects, subjects, abstract ideas, concepts, or the like, including face, car, images, people, emotions, mood, text, natural language, voice, music, video, locations, formulas, facts, historical data, landmarks, personalities, ownership, family, friends, love, happiness, social behavior, voting behavior, and the like, to be used for many applications in our life, including on the search engine, analytics, Big Data processing, natural language processing, economy forecasting, face recognition, dealing with reliability and certainty, medical diagnosis, pattern recognition, object recognition, biometrics, security analysis, risk analysis, fraud detection, satellite image analysis, machine generated data analysis, machine learning, training samples, extracting data or patterns (from the video, images, and the like), editing video or images, and the like. Z-factors include reliability factor, confidence factor, expertise factor, bias factor, and the like, which is associated with each Z-node in the Z-web.

An information retrieval system includes a query revision architecture that integrates multiple different query revisers, each implementing one or more query revision strategies. A revision server receives a user's query, and interfaces with the various query revisers, each of which generates one or more potential revised queries. The revision server evaluates the potential revised queries, and selects one or more of them to provide to the user. A session-based reviser suggests one or more revised queries, given a first query, by calculating an expected utility for the revised query. The expected utility is calculated as the product of a frequency of occurrence of the query pair and an increase in quality of the revised query over the first query.

In one embodiment, navigational features of a navigation device are activated or deactivated according to the accuracy of the geographic data. The navigation features may be predictive features related to upcoming portions of a path curve. The path curve is compared to measured data. For example, a first curve is accessed from a map database and a second curve is based on measured position data collected while traversing the path. The first curve and the second curve correspond to the same geographic area. A difference of an attribute between a section of the first curve and a section of the second curve is used to assign a confidence factor to the section of the first polycurve based on the difference. The attribute may be heading, position, curvature, or another aspect of the path curves.

A method and apparatus for ontology-based classification of media content are provided. With the method and apparatus, initial confidence values of classifiers in a hierarchical classification structure are modified based on relationships between classifiers. A confidence value for a classifier is boosted by a boosting factor based on a correspondence between the confidence value and confidence values of ancestor classifiers in the hierarchical classification structure. A confidence value for a classifier is modified by a confusion factor based on a correspondence between the confidence value of the classifier and the confidence values of mutually exclusive classifiers in the hierarchical classification structure. In this way, a more accurate representation of the actual confidence that media content falls within the classification associated with the classifier is obtained. From this improved classification mechanism, indices for media content may be generated for use in accessing the media content at a later time.

A system, method, and medium for providing configurable item configuration data by receiving a plurality of configuration data sets from a plurality of sources, all which pertain to the same configurable item (CI), then using weighting rules and preferences to assign weight values for each option, feature, and component in each report according to discrepancies and commonalities between the data sets, creating a new data set for the configurable item by selecting options, features, and components having the greatest weight values among all of the data sets, assigning confidence factors to each option, feature, and component by weight comparisons between the plurality of data sets; updating a configuration management database entry for the configurable item accordingly. The confidence factors are useful for inhibiting regulated processes, such as software release processes and change control processes, and for generating human-readable configuration reports indicating confidence levels of the reports and their contents.

Systems and methods to generate business recommendations for specific business actions based on weather element forecasts and known relationships between a business activity and weather elements are provided. The system includes a confidence level filter, an opportunity matrix filter, a weather decision point generator, a business rule recommendation engine and a business rule knowledge database. Methods to generate a business recommendation for a business activity are also provided. The methods include receiving weather driven demand data, assigning opportunity measures to each of the data points, identifying weather decision points based on opportunity measures, and applying business weather rules to the weather decision points to generate business recommendations. In a further feature, a weather element relationship and / or a weather element forecast confidence level is assigned to each data point within the weather driven demand data. These confidence levels are then factored in to determine weather decision points.

A computer-implemented method for targeting marketing content to an online user, includes the steps of collecting data describing the user or the user's ownership item in a user profile, comparing the user profile with a target profile and presenting the user with content based on the comparison. The user profile includes a photographic likeness of the user or the user's ownership item, as well as information derived from the photographic likeness. Certain content may be dynamically created for the user based on the user profile and that content may include the photographic likeness, which may be altered to incorporate a portion of the content into the photographic likeness. In this manner, personalized advertisements for cosmetics, jewelry, clothing, cosmetic procedures, home improvement products, and other products or services may be created. The user profile also includes data describing the user's browsing habits and responses to context-specific survey questions. In one embodiment, metrics are assigned to the user profile data, and a data index identifying the user's preferences and purchasing habits is calculated for the user based on the assigned metrics. Each metric may also have an associated confidence factor, which causes the metric value to decay over time.

A system and a method are provided to quantitatively analyze the risk for a risk-based testing of software having at least one module. The risk-based testing comprises obtaining behavior of each module to a set of test cases. The method to quantitatively analyze the risk comprises assigning a confidence weight to each test case for each module based on its test history, assigning a confidence weight to each of a plurality of software specific parameters for each module, calculating a raw confidence level for each module based on the assigned confidence weights to the test cases, and calculating a confidence quotient for each module as a weighted sum of the raw confidence level for each module and the confidence weight for each software specific parameter. The confidence quotient indicates the risk of defects in each module. The module with the smallest confidence quotient is assigned the highest priority during the testing of the software.

A method is provided for information extraction and classification which combines aspects of local regularities formulation with global regularities formulation. A candidate subset is identified. Then tentative labels are created so they can be associated with elements in the subset that have the global regularities, and the initial tentative labels are attached onto the identified elements of the candidate subset. The attached tentative labels are employed to formulate or “learn” initial local regularities. Further tentative labels are created so they can be associated with elements in the subset that have a combination of global and local regularities, and the further tentative labels are attached onto the identified elements of the candidate subset. Each new dataset is processed with reference to an increasingly-refined set of global regularities, and the output data with their associated confidence labels can be readily evaluated as to import and relevance.

An information retrieval system includes a query revision architecture that integrates multiple different query revisers, each implementing one or more query revision strategies. A revision server receives a user's query, and interfaces with the various query revisers, each of which generates one or more potential revised queries. The revision server evaluates the potential revised queries, and selects one or more of them to provide to the user. A session-based reviser suggests one or more revised queries, given a first query, by calculating an expected utility for the revised query. The expected utility is calculated as the product of a frequency of occurrence of the query pair and an increase in quality of the revised query over the first query.

A device of the present invention obtains a character string of a speech recognition result and a confidence factor thereof. A time monitor monitors time and determines whether or not processing is delayed by checking the confidence factor and time status. When the processing is not delayed, a checker is asked to perform manual judgment. In this event, speech is processed and the manual judgment of the speech recognition result is performed on the basis of the processed speech. When the processing is delayed, automatic judgment is performed by use of the confidence factor. When the character string is judged to be correct as a result of the manual judgment or the automatic judgment, the character string is displayed as a confirmed character string. When the character string is judged to be incorrect, automatic correction is performed by matching on the basis of a next candidate obtained by the speech recognition, texts and attributes of the presentation, a script text, and the like. Character string after the automatic correction is displayed as an unconfirmed character string.

If some aspect of serving or scoring an ad is subject to a performance (e.g., click-through rate, etc.) threshold, such a threshold may be adjusted using a confidence factor of the ad targeting used. For example, ads served pursuant to a more relaxed notion of match might have to meet a higher performance threshold (e.g., than the threshold applied to ads served pursuant to a stricter notion of match). Alternatively, or in addition, ads served pursuant to a stricter notion of match might be subject to a lower performance threshold (e.g., than the threshold applied to ads served pursuant to a more relaxed notion of match). Thus, in general, a performance threshold could increase as match confidence decreases, and / or a performance threshold could decrease as match confidence increases.

Self-asserted socio-demographic attributes of individuals' identities are verified using social network analysis and other means. Through these processes, parties to a transaction or interaction arc provided a measure of confidence about another party's self-asserted socio-demographic attributes, such as age, gender, marital status, etc., in order to assist in determining whether or not to pursue the transaction or interaction. The measure of confidence may be provided as a quantitative “score” indicative of the likelihood the user's self-asserted attribute is actually true. The quantitative score is derived by analyzing a web of trust in which the user is embedded.

A method of operating a vehicle includes determining a pre-crash collision confidence factor and estimating a time to collision. The method further includes deploying a reversible restraint in response to the confidence factor and the time to collision and deploying a non-reversible restraint in response to the confidence factor and the time to collision.

Embodiments of the present disclosure include a method for extracting symbols from a digitized object. The method includes processing the word block against a dictionary. The method includes comparing the word block against a word in the dictionary, the comparison providing a confidence factor. The method includes outputting a prediction equal to the word when the confidence factor is greater than a predetermined threshold. The method includes evaluating properties of the word block when the confidence factor is less than the predetermined threshold. The method includes predicting a value of the word block based on the properties of the word block. The method further includes determining an error rate for the predicted value of the word block. The method includes outputting a value for the word block, the output equal to a calculated value corresponding to a value of the word block having the lowest error rate.

The present invention relates to systems and methods for characterizing targets, e.g., trucks, pallets, trains, cars, and the like, using digital target imaging. Accordingly, embodiments of the present invention provide, at base: a) image segmentation and filtering to identify surrounding white space, interior walls, floor, and ceiling of the container; morphology routines to identify and classify objects found inside the container; and decision routines to report status of container as empty or non-empty with a confidence factor from 1-100.

An autonomous vehicle may be operable in an autonomous mode and a manual mode. A confidence threshold is accessed from a database. The confidence threshold may be associated with a particular geographic area containing the autonomous vehicle. The confidence threshold may be constant for the geographic area accessible by the autonomous vehicle. A computing device calculates a vehicle confidence level based on at least one confidence factor and compares the confidence threshold to the vehicle confidence level. The computing device generates a driving mode command for a vehicle based on the comparison. In one example, the driving mode command transitions the autonomous vehicle to the autonomous mode, if applicable, when the vehicle confidence score exceeds the confidence threshold. In one example, the driving mode command transitions the autonomous vehicle to the manual mode, if applicable, when the vehicle confidence score does not exceed the confidence threshold.

A system and method for automatically altering an image having pixels is disclosed. An image is segmented into regions and various features of the regions are extracted and used to calculate a confidence factor, or belief value, that a particular region is a main subject of the image. The belief values are assembled into a belief map that is used to define how pixel values are to be altered. Various color and appearance values of the pixel are altered in a predetermined way to emphasize the main subject of the image. The emphasis is applied in a binary fashion or as in a gradient of values. Either the main subject can be emphasized, or the secondary or background subjects can be de-emphasized. The system can be implement on a variety of computer systems.

A database has a plurality of entries and a plurality of attributes common to each entry, where each entry corresponds to an individual. A query is received from a querying entity query and is passed to the database, and an answer is received in response. An amount of noise is generated and added to the answer to result in an obscured answer, and the obscured answer is returned to the querying entity. The noise is normally distributed around zero with a particular variance. The variance R may be determined in accordance with R>8 T log2(T / δ) / ε2, where T is the permitted number of queries T, δ is the utter failure probability, and ε is the largest admissible increase in confidence. Thus, a level of protection of privacy is provided to each individual represented within the database. Example noise generation techniques, systems, and methods may be used for privacy preservation in such areas as k means, principal component analysis, statistical query learning models, and perceptron algorithms.

Embodiments of the present disclosure include a method that obtains a digital image. The method includes extracting a word block from the digital image. The method includes processing the word block by evaluating a value of the word block against a dictionary. The method includes outputting a prediction equal to a common word in the dictionary when a confidence factor is greater than a predetermined threshold. The method includes processing the word block and assigning a descriptor to the word block corresponding to a property of the word block. The method includes processing the word block using the descriptor to prioritize evaluation of the word block. The method includes concatenating a first output and a second output. The method includes predicting a value of the word block.

The invention provides various systems and methods for establishing an identity confidence scoring system. The method includes gathering identity information about the customers from physical locations and from remote locations. The method updates the identity profiles with the gathered identity information, and based on the gathered identity information, generates an identity confidence score associated with each identity profile.

A system is described for evaluating the decision-making confidence of a process and system for at least a partial underwriting of insurance policies where placement of an insurance application to an underwriting category is based on its similarity to previous insurance applications. The confidence factor computed is a measure of the correctness of the decision for a given application for insurance.

The invention discloses a model updating method based on strain modal shape correlation. The specific steps are as follows: step 1), establishing a finite element model of a structure and analyzing the finite element model; step 2), performing experimental design and analysis; step 3), extracting a finite element simulation strain mode; step 4), performing correlation analysis: adopting a model confidence factor, and analyzing the correlation between the finite element model and the strain modal shape of an experimental test; step 5), selecting a mode to be modified; step 6), selecting a parameter to be identified; step 7), constructing a modification target; and step 8), performing modified iteration. According to the model updating method based on the strain modal shape correlation provided by the invention, by selecting an appropriate unit type, the obtained finite element model of the structure provides a reference model for strain response calculation; by selecting an appropriate strain mode to be modified, parameters to be modified and an optimum design method, the modified finite element model can better reflect the strain response of the structure; and the accurate finite element model is beneficial to the subsequent structural dynamic optimization design based on the finite element model, and the development of structural health monitoring and structural response prediction and so on.