Abstract: A method for processing risk factors for a user is disclosed. The method may include receiving protocol data for creating a risk factor engine by an application stored and executed at a computing device. The risk factor engine may be stored in memory and executable by a processor to process a first set of stored user health data for a user. The protocol data may include a rule and one or more health attribute values. The rule and the one or more health attribute values may each include a computer programming expression editable by an administrator. The method may further include determining a user health score through execution of the risk factor engine by the processor and based on the user health data.

Abstract: An improved technique uses an expert system to provide automated provisioning of resources for a storage system. Along these lines, a user submits values of a set of provisioning targets parameters in a administrative interface screen to a storage processing device. The expert system uses these values to form a set of facts within an expert system stored on the storage processing device that includes a knowledge base having a set of logical rules and an inference engine. The storage processing device then inputs these facts and logical rules into the inference engine which is configured to fire logical rules having preconditions that match the facts. The actions of these logical rules then provide content for the provisioning of the storage resources, which are displayed to the user or used for automatic storage provisioning operations.

Abstract: Systems and methods are provided for expert systems for well completion using Bayesian decision networks to determine well completion recommendations. The well completion expert system includes a well completion Bayesian decision network (BDN) model that receives inputs and outputs recommendations based on Bayesian probability determinations. The well completion BDN model includes a treatment fluids section, a packer section, a junction classification section, a perforation section, a lateral completion section, and an open hole gravel packing section.

Abstract: A computing device presents a cluster visualization based on a neural network computation. First centroid locations are computed for first clusters. Second centroid locations are computed for second clusters. Each centroid location includes a plurality of coordinate values where each coordinate value relates to a single variable of a plurality of variables. Distances are computed pairwise between each centroid location. An optimum pairing is selected based on a minimum distance of the computed pairwise distances where each pair is associated with a different cluster of a set of composite clusters. Noised centroid location data is created. A multi-layer neural network is trained with the noised centroid location data. A projected centroid location is determined in a multidimensional space for each centroid location as values of hidden units of a middle layer of the multi-layer neural network. A graph is presented for display that indicates the determined, projected centroid locations.

Abstract: Systems and methods are provided for expert systems for well completion using Bayesian decision networks to determine well completion recommendations. The well completion expert system includes a well completion Bayesian decision network (BDN) model that receives inputs and outputs recommendations based on Bayesian probability determinations. The well completion BDN model includes a treatment fluids section, a packer section, a junction classification section, a perforation section, a lateral completion section, and an open hole gravel packing section.

Abstract: Systems, methods, and computer-readable media for generating a data set are provided. One method includes generating a data set based on input data using a plurality of brokers. The method further includes receiving a request from a user and determining whether the request can be fulfilled using data currently in the data set. When the request can be fulfilled using data currently in the data set, the data is accessed using broker(s) configured to provide access to data within the data set. When the request cannot be fulfilled using data currently in the data set, at least one new broker is spawned using existing broker(s) and additional data needed to fulfill the request is added to the data set using the new broker. The method further includes generating a response to the request using one or more of the plurality of brokers.

Abstract: Systems and methods are provided for expert systems for well completion using Bayesian decision networks to determine well completion recommendations. The well completion expert system includes a well completion Bayesian decision network (BDN) model that receives inputs and outputs recommendations based on Bayesian probability determinations. The well completion BDN model includes a treatment fluids section, a packer section, a junction classification section, a perforation section, a lateral completion section, and an open hole gravel packing section.

Abstract: A medical general intelligence computer system and computer-implemented methods analyze morpho-physiological numbers for determining a risk of an emergent disease state, determining an emergent disease state, predicting a pre-emergent disease state, determining a pre-emergent disease state, and/or predicting a risk of a pre-emergent disease state.

Abstract: A system and method to control of sootblowers in a fossil fueled power plant, in particular to plant applications systems using a graphical programming environment in combination with a set of rules to activate sootblowers. The system can be constrained by time limits and/or rule based time limits. Actual blower activation is typically based on the current status of key control variables in the process which alter the actual activation time within a constraints system. The system does not typically require knowledge or models of specific cleanliness relationships. The result is a system without sequences or queues that readily adapts to changing system conditions.

Abstract: Techniques to optimize messages sent to a user of a social networking system. In one embodiment, information about the user may be collected by the social networking system. The information may be applied to train a model for determining likelihood of a desired action by the user in response to candidate messages that may be provided for the user. The social networking system may provide to the user a message from the candidate messages with a selected likelihood of causing the desired action.

Abstract: An improved content search mechanism uses a graph that includes intelligent nodes avoids the overhead of post processing and improves the overall performance of a content processing application. An intelligent node is similar to a node in a DFA graph but includes a command. The command in the intelligent node allows additional state for the node to be generated and checked. This additional state allows the content search mechanism to traverse the same node with two different interpretations. By generating state for the node, the graph of nodes does not become exponential. It also allows a user function to be called upon reaching a node, which can perform any desired user tasks, including modifying the input data or position.

Abstract: One embodiment of the present invention provides a system for generating a product recommendation. During operation, the system receives graph data indicating vertices and edges of the graph. The vertices represent customers and products and the edges represent purchases. The system then receives a query of the graph to determine a product recommendation. Next, the system generates a finite-state machine (FSM) based on the query, executes the query, and determines whether a current state of the FSM is a traversal state. In response to the current state being a traversal state, the system generates a traversal FSM. The system then searches the traversal FSM for a nearest future traversal state, generates a bitmask for the future traversal state, and utilizes the generated bitmask when executing the future traversal state to generate the product recommendation.

Abstract: A method of determining a short term driving tendency and a system of controlling shift using the same that reflects precisely a will of a driver on the shift by determining a short term driving tendency is disclosed. The method may include detecting input variables, determining whether determination condition of the short term driving tendency is satisfied, calculating tendencies and output membership function values according to a plurality of fuzzy rules based on the input variables if the determination condition of the short term driving tendency is satisfied, and determining a short term driving tendency index based on the tendencies and the output membership function values according to the plurality of fuzzy rules.

Abstract: A computer-implemented method for identifying relationships between entities includes accessing a first data structure being a two-dimensional array of scalar elements (e, eij, ekl(i)) representable as a matrix, each of the scalar elements capturing a relationship between two entities; reorganizing the first data structure by clustering the scalar elements separately on each dimension of the two-dimensional array, to obtain a second data structure, representable as a K×M block matrix, wherein each block is a reordered sequence of rows and/or columns of the first data structure; compacting the second data structure by: determining two parallel block sequences, which are the most similar according to a given distance measure, the parallel block sequences being either distinct rows or distinct columns of blocks of the second data structure; and reorganizing the second data structure by merging the two determined sequences into a single block sequence.

Abstract: Techniques are described herein for predicting one or more behaviors by an email recipient and, more specifically, to machine learning techniques for predicting one or more behaviors of an email recipient, changing one or more components in the email to increase the likelihood of a behavior, and determining and/or scheduling an optimal time to send the email. Some advantages of the embodiments disclosed herein may include, without limitation, the ability to predict the behavior of the email recipient and suggest the characteristics of an email which will increase the likelihood of a positive behavior, such as a reading or responding to the email, visiting a website, calling a sales representative, or opening an email attachment.

Abstract: Methods and systems for Web-scale entity relationship extraction are usable to build large-scale entity relationship graphs from any data corpora stored on a computer-readable medium or accessible through a network. Such entity relationship graphs may be used to navigate previously undiscoverable relationships among entities within data corpora. Additionally, the entity relationship extraction may be configured to utilize discriminative models to jointly model correlated data found within the selected corpora.

Abstract: Methods and apparatus for determining whether a media presentation device is in an on state or an off state are disclosed. A disclosed example method comprises determining first and second characteristics of a signature associated with a signal representative of media content presented via a media presentation device, evaluating the first and second characteristics to determine first and second fuzzy contribution values representing, respectively, degrees with which the first and second characteristics correspond to the media presentation device being in at least one of an on state or an off state, determining a third fuzzy contribution value based on a number of the first and second contribution values indicating the media presentation device is in one of the on or off states, and combining the first, second and third fuzzy contribution values for use in determining whether the media presentation device is in the on state or the off state.

Abstract: A dialog manager receives previous user actions and previous observations and current observations. Previous and current user states, previous user actions, current user actions, future system actions, and future observations are hypothesized. The user states, the user actions, and the user observations are hidden. A feature vector is extracted based on the user states, the system actions, the user actions, and the observations. An expected reward of each current action is based on a log-linear model using the feature vectors. Then, the current action that has an optimal expected reward is outputted.

Abstract: Methods, systems and computer program products are provided for generating a feasibility score for a job search and for generating a suggestion for enhancing the score. In one method, one or more computing devices receive, over a network, a data object that is associated with a user who is engaged in a search for employment. The data object includes a résumé of the user and a requirement that is associated with the search. The computers calculate, based on the data object, a score that indicates a likelihood of receiving an offer for an employment position that satisfies the requirement. The computers generate a suggestion that identifies how the score may be increased. The computers send the suggestion over the network to a computing device of the user.

Abstract: Quantitative analysis is provided through the implementation of a graph that includes nodes having edges therebetween representing data dependencies between the nodes. The nodes include calculation objects such as programs, data, libraries, and/or other objects. The nodes provide for modular computation that provides for transparency, record-keeping, experimentation, and/or other functionalities.