2271 results about "Inference" patented technology

A Software Fault Management (SFM) system for managing software faults in a managed mobile telecommunications network. The SFM system includes an Intelligent Management Information Base (I-MIB) comprising a Management Information Base (MIB) and a Knowledge Base (KB) having a functional model of the managed network and a trouble report / known faults (TR / KF) case base. The SFM system also includes an intelligent multi-agent portion having a plurality of agents which process the software faults utilizing the functional model from the I-MIB, case-based information, and other management information. The I-MIB and the intelligent multi-agent portion are compliant with Telecomunications Management Network (TMN) principles and framework. Fault management is both proactive and reactive. The SFM system is made independent of technology-specific implementations by representing the underlying switch design knowledge in a modular and changeable form which is then interpreted by the intelligent multi-agent portion. A clear separation is maintained between the generic procedural inference mechanisms and agents, and the specific and explicit models of the different network elements of a mobile telecommunications network.

A system and method for supporting Product Lifecycle Management over a distributed service network topology that connects a hierarchy of functional domains, each domain having a service ontology and one or more service composition schemas defined by the service ontology. Each service composition schema models a business process in its domain. Descriptions of services provided to each domain are published to a service repository by providers of the services, in conformity with one of the service composition schemas. There is a business process proxy provided by the service provider for each service description, which encapsulates for public access the internal processes of the service provider. The invention makes use of an event messaging protocol that enables service collaboration and ad-hoc workflow composition. Each business process is implemented by an ad-hoc workflow comprised of one or more tasks connected by one or more business rules. For each business process there is a business flow manager that dynamically composes ad-hoc workflow prior to execution and dynamically modifies the ad-hoc workflow as the business process executes. The business flow manager uses backward-chain inferencing and then forward-chain inferencing to generate the ad-hoc workflows, based on user identification of a target task. The business flow manager is able to stop execution of the workflow and regenerate a workflow for remaining tasks in response to events received over the network from service providers, and is also able to detect conflicts in the workflows at composition time and at execution time.

A smart agent (SA) is provided which resides locally in a local client device and by iterative means integrates the habit, statistics and psycho-demographic information of a user to infer the user's preferences. The SA may also utilize the preferences to filter information delivered to the local device. The invention further discloses a means of collecting, combining, integrating and inferring information from the user to arrive at a psycho-demographic profile of the user, and a means of utilizing such psycho-demographic profile to select or filter information delivered to the user, thereby achieving targeting. The invention also discloses a means of classifying and identifying the information delivered so that it can be matched, filtered or selected.

The present invention is directed to a system and method for correlating an image with information associated with the image comprising identifying image metadata for the image, wherein the image metadata includes information associated with conditions at the time of image capture, searching one or more information sources using parameters in the image metadata to collect inference information from the information sources, and displaying the inference information to a user.

An interactive navigation system includes a navigation processing unit, a current position sensor, a speaker, a microphone and a display. When it is preliminary inferred, based on receipt of a detection signal from the sensor, that a vehicle has probably been diverted from a drive route determined by the navigation processing unit, a machine voice question is produced through the speaker for confirmation of the inferred probability of diversion. A driver or user in the vehicle answers the question, which is input through the microphone and analyzed to be affirmative or negative, from which a final decision is made as to the vehicle diversion. In a preferred embodiment the question is spoken by a personified agent who appears on the display. The agent's activities are controlled by an agent processing unit. Communication between the agent and the user improves reliability and accuracy of inference of any vehicle condition which could not be determined perfectly by a sensor only.

A method of detecting malicious activity, including the steps of: intercepting activity in a processing system 100; detecting attributes of an un-assessed process 460 associated with the activity; comparing the process attributes and activity to a database 430 of attributes and activity associated with known malicious and non-malicious processes; and using an inference filter 470 to compute the likely maliciousness of the un-assessed process.

A digital computer and method for processing data indicative of images of facial and head movements of a subject to recognize at least one of said movements and to determine at least one mental state of said subject is provided. The outputting instructions for providing to a user information relating to at least one said mental state. A further processing data reflective of input from a user, and based at least in part on said input, confirming or modifying said determination and generating with a transducer an output of humanly perceptible stimuli indicative of said at least one mental state.

A system and method for protecting user privacy using social inference protection techniques is provided. The system executes a plurality of software modules which model of background knowledge associated with one or more users of the mobile computing devices; estimate information entropy of a user attribute which could include identity, location, profile information, etc.; utilize the information entropy models to predict the social inference risk; and minimize privacy risks by taking a protective action after detecting a high risk.

The present invention is directed to a method for inferring / estimating missing values in a data matrix d(q, r) having a plurality of rows and columns comprises the steps of: organizing the columns of the data matrix d(q, r) into affinity folders of columns with similar data profile, organizing the rows of the data matrix d(q, r) into affinity folders of rows with similar data profile, forming a graph Q of augmented rows and a graph R of augmented columns by similarity or correlation of common entries; and expanding the data matrix d(q, r) in terms of an orthogonal basis of a graph Q×R to infer / estimate the missing values in said data matrix d(q, r).on the diffusion geometry coordinates.

Methods of applying adaptive social computing systems are disclosed. The social computing systems include capabilities to generate adaptive recommendations and representations of social networks derived, at least in part, from inferences of the preferences and interests of system users based on a plurality of usage behaviors, spanning a plurality of usage behavior categories. The behavioral categories include system navigation behaviors, content referencing behaviors, collaborative behaviors, and the monitoring of physical location and changes in location. Privacy control functions and compensatory functions related to insincere usage behaviors can be applied. Adaptive recommendation delivery can take the form of visual-based or audio-based formats.

Non-Subjective Valuing ©& is a computer-assisted valuing system for discovering both an entity's actual current societal monetary value and its contemporary monetary worth specifically to the inquiring individual person, group or corporation, providing a user with such target entity's retail and wholesale prices along with its true worth and specific value to the explorer, employing as yardstick the NORM, which is the hypothetical unit in any group that is accurately calculated to be both precisely average in every one of its collectively discoverable characteristics and its price, to which NORM yardstick the present invention compares any test unit in that group on a natural, quantified point basis to obtain such precise current monetary worth of any such test unit, employing a specially conceived, designed and explained organic application of inductive statistics, accurate sampling, central tendency, and statistical inference, for calculating; drawing scientifically valid conclusions about surveying a constantly and factually representative community (such as the United States, 1999, for example), combined with certain new discoveries and unique, novel processes, as set forth herein, enabling Non-Subjective Valuing ©& instantly and conclusively to empower a prospective trader objectively to compare the contemporary monetary values of any and all competing units in or out of any probed group, regardless of such competing units' respective current prices.

Described is a technology by which raw GPS data is processed into segments of a trip, with a predicted mode of transportation (e.g., walking, car, bus, bicycling) determined for each segment. The determined transportation modes may be used to tag the GPS data with transportation mode information, and / or dynamically used. Segments are first characterized as walk segments or non-walk segments based on velocity and / or acceleration. Features corresponding to each of those walk segments or non-walk segments are extracted, and analyzed with an inference model to determine probabilities for the possible modes of transportation for each segment. Post-processing may be used to modify the probabilities based on transitioning considerations with respect to the transportation mode of an adjacent segment. The most probable transportation mode for each segment is selected.

A system and method for identifying ideal channels for communications based on an analysis of communication channel reliability, communicating party preferences, and communicating party contexts is provided. The system attempts to optimize the utility of a communication based on inferred or directly accessed channel reliability data, communicating party preferences and communicating party contexts. Such optimization can be achieved using reliabilities, preferences and policies concerning handling the attempted contact based on a deterministic specification or through inferring reliability, context, content and task under uncertainty by employing decision-theoretic inferences. The methods may consider channels currently available as well as channels available at later times. Thus, the service can include automated rescheduling of communications based on a consideration of forecasts of reliability and availability. The approach may include the use of forecasts about the time required for a communication and the likelihood that a connection will be dropped or will lose fidelity over this period of time. The methods may also include a consideration of metadata within a standard schema that is transmitted along with a communication attempt, the metadata representing information about attributes like the potential communication channels, the identity of the contactor, the task at hand, and the context of the communicating parties. The invocation of the communication service may be performed in a variety of ways, including single button invocations, and via a communication service that is more deeply integrated with other applications and functionalities.

A system and method for representing, storing and retrieving real-world knowledge on a computer or network of computers is disclosed. Knowledge is broken down into permanent atomic “facts” which can be stored in a standard relational database and processed very efficiently. It also provides for the efficient querying of a knowledge base, efficient inference of new knowledge and translation into and out of natural language. Queries can also be processed with full natural language explanations of where the answers came from. The method can also be used in a distributed fashion enabling the system to be a large network of computers and the technology can be integrated into a web browser adding to the browser's functionality.

What is proposed is a method of implementing a security system (Packet Sentry) addressing the internal security problem of enterprises having a generalized approach for inferential determination and enforcement of network policy with directory service based group correlation with transparent authentication of the connected customer and the policy enforcement inside the network. The security system enables the network to analyze and enforce policy using any bit or bits in a stream or a packet, conduct Flow Vector analysis on the data traffic, provide Application Monitoring, Normalization and user authentication validation. The system enables the network to implement Group relationship Analysis and correlation using combination of Network inferences and Directory service data resulting in generation of Group norms using statistically significant relationships. These will provide a more secure enterprise environment where data security levels can be enforced and the usage monitored effectively in the infrastructure.

A system and method for personalizing an interactive voice output of a voice service based on determinations about the caller or call, the output containing information derived from on line analytical processing (OLAP) systems, where content stored in the database can be readily obtained by a requester on the fly and in a personalized, interactive manner. The system and method include a call server for receiving an incoming call from a caller, an inference module for determining information about a voice service to be provided to the caller, a control module related to the information determined and for facilitating the interactive voice broadcast with the caller, and a personalization module for passing determined information to the control module.

Data mining for managing marketing resources is disclosed. In one embodiment, a method for managing a marketing campaign includes the following. First, the method provides a data mining engine capable of being trained with training data and capable thereof of performing inference relative to the training data and on future data. Next, the method provides a user database defining observed characteristics of each one of a set of users. The characteristics include at least one of one or more user's attributes, and one or more of the user's preferences. Finally, the data mining engine is trained with a set of training data comprising the user data base, and a predetermined characteristic pertaining to the market campaign is input to the engine, such that, in response to the input, a subset of the users in the database is obtained that have the highest correlation to the characteristic.

A data collection system that provides the means to collect, store and make data available for a location analytics inference pipeline. The system incorporates a feedback mechanism enabling algorithms produced from the inference pipeline to drive the collection strategy to yield higher data quality and to produce reference data for model validation.

The present invention is directed to a method for inferring / estimating missing values in a data matrix d(q, r) having a plurality of rows and columns comprises the steps of: organizing the columns of the data matrix d(q, r) into affinity folders of columns with similar data profile, organizing the rows of the data matrix d(q, r) into affinity folders of rows with similar data profile, forming a graph Q of augmented rows and a graph R of augmented columns by similarity or correlation of common entries; and expanding the data matrix d(q, r) in terms of an orthogonal basis of a graph Q×R to infer / estimate the missing values in said data matrix d(q, r) on the diffusion geometry coordinates.

Sensors detect machine parameters such as vibration, turning speed, and temperature, and a local processor performs logic operations based on the parameters and inference rules to produce fault information that is reported to a system processor, which selectively uses the fault information to control the plant machines. The inference rules include rules for determining faults as to balance, alignment, bearing condition, electrical condition, and cavitation. The inference rules are contained in rules code that is separate from the analysis code that performs the logical operations. Thus, the inference rules may be easily changed without changing other code, such as the analysis code.

In scalable video coding where two predictive motion vectors are calculated: one from the current layer neighboring motion vectors and one from the co-located base layer motion vectors. One of the two predictive motion vectors is chosen as the predictive motion vector for current block. A flag bit is coded to indicate which predictive motion vector is chosen only if it is not possible to infer the layer from which the predictive motion vector for the current block comes. Such inference is possible in many situations, such as when both predictive motion vectors are substantially the same, or only one of the vectors is reliable or available.

An adaptive system applied to social network and process network applications is disclosed. These adaptive social networking and tagging systems, and adaptive process network systems, apply algorithms for monitoring user usage behaviors across a plurality of usage behavior categories associated with a computer-based system, and generating recommendations based on inferences on user preferences and interests based, at least in part, on usage behaviors. Additional functions for effectively and efficiently managing social and process networks, such as social network measurement and analysis features, community tagging functions, and process network recombination functions are also described.

Traffic measurement should make it possible to obtain the spatial flow of traffic through the domain, i.e., the paths or trajectories followed by packets between any ingress and egress point of the domain. A method of sampling packet trajectories in a packet switching network allows the direct inference of traffic flows through a measurement domain by observing the trajectories of a subset of all packets traversing the network. A method which assumes that the measurement domain does not change comprises the steps of selecting packets for sampling in accordance with a sampling function of the packet content and generating a practically unique label for each sampled packet. The method does not rely on routing state, its implementation cost is small, and the measurement reporting traffic is modest and can be controlled precisely. Using the same hash function will yield the same sample set of packets in the entire domain, and enables us to reconstruct packet trajectories. An alternate embodiment which assumes no constraints and that the measurement domain may change comprises the steps of applying a sampling function and altering an invariant bit position as a signaling flag in each packet selected for sampling.

Techniques for creating and utilizing cohort groups help to facilitate connectedness. Cohort groups can be created, built and utilized to identify parties that could and / or should be connected. The cohort groups can be easily and quickly created and modified both passively and actively, through automated and semi-automated means. Users provide profile information to the system. The system can generate cohort groups based on the provided information, as well as updated information, relationship rules between the information, geographic locations of the users, semantic processing, advanced inferences (such as artificial intelligence or other techniques), and self-identified affiliations.

The present invention is related to a system and method of caching data employing probabilistic predictive techniques. The system and method has particular application to multimedia systems for providing local storage of a subset of available viewing selections by assigning a value to a selection and retaining selections in the cache depending on the value and size of the selection. The value assigned to an item can represent the time-independent likelihood that a user will review an item at some time in the future. An initial value of an item can be based on the user's viewing habits, the user's viewing habit over particular time segment (e.g., early morning, late morning, early afternoon, late afternoon, primetime, late night) and / or viewing habits of a group of user's during a particular time segment. A value assigned to a selection dynamically changes according to a set of cache retention policies, where the value can be time-dependent functions that decay based on the class of the item, as determined by inference about the class or via a label associated with the item. A selections value may be reduced as the selection ages because a user is less likely to view the selection over time. Additionally, a value of a selection may change based on changes on a user's viewing habits, changes in time segments or a user's modification of the cache retention policies.

The present invention relates to a system and methodology to facilitate collaboration and communications between entities such as between automated applications, parties to a communication and / or combinations thereof. The systems and methods of the present invention include a service that supports collaboration and communication by learning predictive models that provide forecasts of one or more aspects of a users' presence and availability. Presence forecasts include a user's current or future locations at different levels of location precision and usage of different devices or applications. Availability assessments include inferences about the cost of interrupting a user in different ways and a user's current or future access to one or more communication channels. The predictive models are constructed from data collected by considering user activity and proximity from multiple devices, in addition to analysis of the content of users' calendars, the time of day, and day of week, for example. Various applications are provided that employ the presence and availability information supplied by the models in order to facilitate collaboration and communications between entities.

Information about a person's interests and gaming behavior may be determined by monitoring their online gaming activities (and perhaps making inferences from such activities). Such information may be used to improve ad targeting. For example, such information may used to target ads to be rendered in a video game being played by the person.

An adaptive recommendation system and a mobile adaptive recommendation system are disclosed. The adaptive recommendation system and the mobile adaptive recommendation system include algorithms for monitoring user usage behaviors across a plurality of usage behavior categories associated with a computer-based system, and generating recommendations based on inferences on user preferences and interests. Privacy control functions and compensatory functions related to insincere usage behaviors can be applied. Adaptive recommendation delivery can take the form of visual-based or audio-based formats.

A system and method of advertising in computer-implemented social networks is disclosed. The influence level of members of the social network and explicit and inferred relationships among members are determined. Advertisements are delivered in association with content objects representing one or more members of the social network, where the content objects may include member profiles, as well as other content that is associated with the member. Selection of the advertisements may be based on inferences of member interests derived from system usage behaviors, as well as explicit indicators of members' interests and preferences.

A method and system for automated generation of social networks. A graphical user interface receives a user query for an entity of interest, and outputs a graphical network showing entities and associations related to the entity of interest. A search engine interface transmits the query to a search engine, and receives references to documents. A named entity extractor downloads a selection of the documents, and generates a list of named entities referenced in the downloaded documents. A network inference module receives each list of named entities, and generates associations between the named entities in each list. An entity matcher operates on the associations to consolidate them in instances wherein differently named entities are determined to be the same named entity, and provides a consolidated list of named entities and associations to the user interface for display as a graphical network.