1150 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.

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.

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.

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.

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.

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.

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 sensing and context management architecture that can detect that a user is interacting with a given device and in an associated context, and in response thereto, manages device processes as the user moves from device to device, location to location, and/or context to context. The invention comprises a system that facilitates management of a user situation or context. A sensing component is provided that senses a context of a user by way of one or more sensors and/or a particular device with which the user is interacting in the context, for example, and a management component that manages the device and/or one or more services in the context according to rules or inferences user preferences, sensed observations, and user input data.

A method and system for optimizing routing traffic to a destination when multiple routes are available. A performance monitoring and inference component measures the performance of the available paths to a large set of subnetworks, and uses those measurements to infer the performance of all available paths to an even larger set of subnetworks. A routing optimization component uses a cost function that assigns a cost to a routing table based on information from the performance monitoring and inference component, as well as other path characteristics, and further uses a minimization methodology to find a routing table with a very low cost, as defined by the cost function. A BGP bridge takes the routing table generated by the routing optimization component and communicates that information to the routers using BGP, thereby ensuring that the routers will route traffic in accordance with the routing table.

A method and computer-readable medium are provided for identifying clean signal feature vectors from noisy signal feature vectors. The method is based on variational inference techniques. One aspect of the invention includes using an iterative approach to identify the clean signal feature vector. Another aspect of the invention includes using the variance of a set of noise feature vectors and/or channel distortion feature vectors when identifying the clean signal feature vectors. Further aspects of the invention use mixtures of distributions of noise feature vectors and/or channel distortion feature vectors when identifying the clean signal feature vectors. Additional aspects of the invention include using a variance for the noisy signal feature vector conditioned on fixed values of noise, channel transfer function, and clean speech, when identifying the clean signal feature vector.

Method and system for analyzing relationship between molecular structure and biological activity in one or more molecules by transforming molecular structure data into a hierarchical representation of chemical concepts and descriptors and detecting common tree-like patterns in the data.

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.

A method of speech recognition obtains acoustic data from a plurality of conversations. A plurality of pairs of utterances are selected from the plurality of conversations. At least one portion of the first utterance of the pair of utterances is dynamically aligned with at least one portion of the second utterance of the pair of utterance, and an acoustic similarity is computed. At least one pair that includes a first portion from a first utterance and a second portion from a second utterance is chosen, based on a criterion of acoustic similarity. A common pattern template is created from the first portion and the second portion.

Embodiments of the present invention enable dynamic repartitioning of data storage in response to one or more triggers. In embodiments, a trigger may be a user-initiated action, a system-generated action, and/or an inference based on storage usage parameters. Applications of the present invention are its use in embodiments of a storage management system comprising a file system manager and a volume manager, where the placement of data into a partition (data storage region) may be specified by matching one or more disk region placement data attributes assigned to data with corresponding disk region attributes. In embodiments, dynamic repartitioning comprises adjustment of the location of the boundary between adjacent disk partitions and, if necessary, rebalancing of the data stored within the partitions by identifying mismatched data and relocating it to the partition with which it is associated.

An ontology-based ad hoc service discovery system includes a local service cache, a cache manager, a service description unit, a query processor, a service semantic inference unit and a node daemon. The local service cache restores a service ontology by collecting class information of all services advertised on an ad hoc network and stores the service ontology. The cache manager manages the local service cache and performs various preset operations on the cache. The service description unit stores a description of a corresponding service for use in initializing the local service cache. The query processor starts performing a semantic based service query protocol by receiving a service query from a user or an application program. The service semantic inference unit inspects whether the service query transmitted from a client is coincident with the content of the service. The node daemon performs a service cache synchronization protocol with neighboring nodes.

Aspects discussed herein present a solution for utilizing large-scale knowledge graphs for inference at scale and generating explanations for the conclusions. In some embodiments, aspects discussed herein learn inference paths from a knowledge graph and determine a confidence score for each inference path. Aspects discussed herein may apply the inference paths to the knowledge graph to improve database lookup, keyword searches, inferences, etc. Aspects discussed herein may generate a natural language explanation for each conclusion or result from one or more inference paths that led to that conclusion or result. Aspects discussed herein may present the best conclusions or results to the user based on selection strategies. The presented results or conclusions may include generated natural language explanations rather than links to documents with word occurrences highlighted.

A mechanism for compiling a generative description of an inference task into a neural network. First, an arbitrary generative probabilistic model from the exponential family is specified (or received). The model characterizes a conditional probability distribution for measurement data given a set of latent variables. A factor graph is generated for the generative probabilistic model. Each factor node of the factor graph is expanded into a corresponding sequence of arithmetic operations, based on a specified inference task and a kind of message passing algorithm. The factor graph and the sequences of arithmetic operations specify the structure of a neural network for performance of the inference task. A learning algorithm is executed, to determine values of parameters of the neural network. The neural network is then ready for performing inference on operational measurements.

A Cooperative Help Assistance (CHA) system and method provide real-time user assistance for one or more windows-based Graphic User Interface (GUI) applications or a single application's different subsections such as web pages, running concurrently in any operating system. The CHA System enables the development of an informative assistance object independently from the original source code or development environment of the target Host Application. The assistance object can be selected by any number of user interfaces from sophisticated inference driven interactive interface search tools or categorized lists. By intercepting and monitoring user actions on a Host Application, the CHA system performs intelligent assistance in the context of the target host application program. Utilizing a Host Application Model, the CHA System and method dynamically assemble many elements in real-time or just-in-time to produce assistance sequences or elements very efficiently without having to code every interface path permutation. Paths can be dynamically generated from the Host Application Model, which enables a real-time module to offer intelligent, contextual assistance as well as real-time construction of automated, accelerated CHA Sequences or Procedures that require little or no user interaction. All assistance and information are processed and expressed by an extensive multitasking, multimedia subsystem for two dimensional (2D) and real-time three-dimensional (3D) application interfaces, which greatly enhances and extends the effectiveness of any explanation or material expression. The production of Assistant Sequences is facilitated by the Host Application Model and 2D and 3D GUI “drag and drop” interface tools.

The present invention is to provide a learning machine capable of expressing/accumulating concept and semantic relation by understanding semantic relation of information as a relation between concepts after characteristics, semantic relation and structure of information and the like have been analyzed. The present invention is intended to realize a thinking machine in which information is inclusively collected and stored as knowledge structured based on the semantic relation of the collected information, information is generated by predetermined inference so as to have a new semantic relation in response to an inquiry or request and which can decide an optimal solution to an inquiry and the like by evaluating/deciding new generated information.

This invention teaches a multi-sensor quality inference system for additive manufacturing. This invention still further teaches a quality system that is capable of discerning and addressing three quality issues: i) process anomalies, or extreme unpredictable events uncorrelated to process inputs; ii) process variations, or difference between desired process parameters and actual operating conditions; and iii) material structure and properties, or the quality of the resultant material created by the Additive Manufacturing process. This invention further teaches experimental observations of the Additive Manufacturing process made only in a Lagrangian frame of reference. This invention even further teaches the use of the gathered sensor data to evaluate and control additive manufacturing operations in real time.