Abstract: The present invention provides a method for updating betweenness centrality of a graph, which obtains the betweenness centrality of an unweighted graph, which is updated when edges are updated. First of all, the method is performed by obtaining a minimum union cycle (an MUC) of the updated graph, and extracting an MUC (MUCU) containing a vertex, which is incident to the updated edge. And a first betweenness centrality due to the shortest paths in the MUCU, and a second betweenness centrality due to the shortest paths, not included in the MUCU, are calculated. And finally, a final betweenness centrality of the graph is obtained by adding the first and second betweenness centralities. By using the method, the search space and calculation cost can be remarkably reduced.

Abstract: A system and method is described for use with a data grid cluster, which uses cluster quorum to prevent split brain scenario. The data grid cluster includes a plurality of cluster nodes, each of which runs a cluster service. Each cluster service collects and maintains statistics regarding communication flow between its cluster node and the other cluster nodes in the data grid cluster. The statistics are used to determine a status associated with other cluster nodes in the data grid cluster whenever a disconnect event happens. The data grid cluster is associated with a quorum policy, which is defined in a cache configuration file, and which specifies a time period that a cluster node will wait before making a decision on whether or not to evict one or more cluster nodes from the data grid cluster.

Abstract: Methods and arrangements for conducting a search using query logs. A query log is consulted and query rewrite rules are learned automatically based on data in the query log. The learning includes obtaining click-through data present in the query log.

Abstract: A method, system and computer program product are disclosed for predicting influence in a social network. In one embodiment, the method comprises identifying a set of users of the social network, and identifying a subset of the users as influential users based on defined criteria. A multitude of measures are identified as predictors of which ones of the set of users are the influential users. These measures are aggregated, and a composite predictor model is formed based on this aggregation. This composite predictor model is used to predict which ones of the set of users will have a specified influence in the social network in the future. In one embodiment, the specified influence is based on messages sent from the users, and for example, may be based on the number of the messages sent from each user that are re-sent by other users.

Abstract: Described is a recall system that uses spiking neuron networks to identify an unknown external stimulus. The system operates by receiving a first input signal (having spatial-temporal data) that originates from a known external stimulus. The spatial-temporal data is converted into a first spike train. A first set of polychronous groups (PCGs) are generated as a result of the first spike train. Thereafter, a second input signal originating from an unknown external stimulus is received. The spatial-temporal data of the second input signal is converted into a second spike train. A second set of PCGs are then generated as a result of the second spike train. Finally, the second set of PCGs is recognized as being sufficiently similar to the first set of PCGs to identify the unknown external stimulus as the known external stimulus.

Abstract: A system and method is described for use with a data grid cluster, which uses cluster quorum to prevent split brain scenario. The data grid cluster includes a plurality of cluster nodes, each of which runs a cluster service. Each cluster service collects and maintains statistics regarding communication flow between its cluster node and the other cluster nodes in the data grid cluster. The statistics are used to determine a status associated with other cluster nodes in the data grid cluster whenever a disconnect event happens. The data grid cluster is associated with a quorum policy, which is defined in a cache configuration file, and which specifies a time period that a cluster node will wait before making a decision on whether or not to evict one or more cluster nodes from the data grid cluster.

Abstract: Particular embodiments use roles to determine anomalies in a user's behavior. Different roles may be defined for a business. For example, users that have similar job responsibilities are grouped in a role. Behavior information is then monitored for the plurality of users in the role. This may include transactions or other actions taken by the user. Over time, a profile can be generated for the user based on the monitored behavior. This profile learns the user's behavior. Information for the user's behavior may then be compared to other users' profiles in the same role to determine anomalies in the user's behavior over time. For example, when differences in activities occur for a user as compared to other users with the same role, a message may be generated that indicates that there may be an anomaly in the user's behavior. This alert may then be output.

Abstract: Exemplary embodiments described herein are directed to systems and methods that estimate a user's affect and communication preferences from presence data. The exemplary embodiments use a small set of features derived from a user's recent high level presence states. Exemplary embodiments also use features from broader classes of presence data. Utilizing features from a combination of presence data and recent presence states may provide improvement over estimates that users are able to make themselves. The exemplary embodiments further consider cost, burden on the user, and privacy issues in estimating affect and communication preferences.

Abstract: Records of events associated with network entities in a network environment are received, where the network entities are selected from hardware entities, software entities, and combinations of hardware and software entities. The records of the events are identified to identify relationships between events associated with different ones of the network entities, where the records of the events identify corresponding network entities impacted by the events. A Bayesian network is constructed based on the analyzing, wherein the constructed Bayesian network is able to make predictions regarding relationships between events associated with the network elements.

Abstract: A data processing system, computer program, and method for providing a response to a statement of a user before receiving a complete user statement involves, in response to receiving a partial user input, calculating for each of a plurality of predefined answerable statements, a metric based on a frequency with which the predefined answerable statement had been selected by previous users. If the metrics for none of the predetermined answerable statements exceed a threshold, the computer sends the user suggested predefined answerable statements. If one of metrics exceeds the threshold, and not otherwise, the computer sends the user information representative of a response to the predefined answerable statement associated with that metric.

Abstract: Disclosed herein is a computer implemented method and system for analyzing load responsive behavior of infrastructure components in an electronic environment for proactive management of the infrastructure components. Transaction data on multiple application transactions is collected. Load patterns are identified from the collected transaction data for generating load profiles. Data on infrastructure behavior in response to the application transactions is collected. Infrastructure behavior patterns are identified from the infrastructure behavior data for generating behavior profiles. The generated load profiles and the generated behavior profiles are correlated to create a load responsive behavior model. The created load responsive behavior model predicts behavior of the infrastructure components for different load patterns. A live data stream from current application transactions is analyzed using the load responsive behavior model to determine current load responsive behavior.

Abstract: Content items, such as e-books, audio files, video files, etc., may be recommended to a user based on the user's presence at a geolocation or venue. Geolocation is the geospatial location of the user, while a venue is a designated area for an activity, such as a concert hall, aircraft, waiting room, etc. The recommendations may be of content items relating to the geolocation or venue, or they may be content items being accessed by others who are, or have been, in approximately the same geolocation or venue.

Abstract: Exemplary methods and apparatuses are provided which may be used for classifying and indexing segmented portions of web pages and providing related information for use in information extraction and/or information retrieval systems.

Abstract: An apparatus includes an analytic network process (ANP) storage memory that stores an ANP model populated with data, the ANP model having feedback connections in place among nodes within the ANP model, and a processor in communication with the ANP storage memory. The processor is configured to facilitate selecting one or more metrics to use to determine influence of criteria within the ANP model. Also, the processor determines a combined influence score, the combined influence score being a single score for each of the criteria in the ANP model. Also, the processor determines which of the criteria in the ANP model is most influential among the criteria in the ANP model, for the one or more metric which is selected to use to determine the influence of the nodes in the ANP model.

Abstract: A method and system of determining a prioritized list of one or more users related to a given goal obtaining a set of places, determine one or more future places an expert associated with a given goal is predicted to visit to accomplish the given goal, obtain a history of one or more places users have visited, determine one or more historical places from the history of one or more places that match the future places, and identify one or more users associated with the determined one or more historical places.

Abstract: A system and method are provided for psychographically profiling a target population of individuals, programmably implemented in a server apparatus. The psychographic segmentation portion includes a questionnaire processing part, a segment solution part, and a typing tool part. The questionnaire processing part acquires a plurality of responses to a predetermined set of questionnaire questions by an initial pool of target population members. The questionnaire processing part uses a combination of weighted statistical methodologies to arrive at a rule-based decision on whether the question would serve as a good wedge variable. Optionally, the rule based decision is then compared to an expert's opinion and the weights and threshold parameters of the weighted statistical combination are adjusted accordingly to more accurately match the expert's decision. The identified wedge variables are used for effectively segregating the target population into groups of homogenous individuals.

Abstract: Systems and methods for choice experiments to model user behavior are disclosed. Choice experiment surveys require respondents to choose by performing trade-offs between combinations of features included in alternatives under consideration. Users specify constraints and an attribute space of features to investigate, and generate candidate experimental designs based on the constraints and attributes. Users select an optimum design tailored to the problem to be solved, instead of having to modify their problem to match a known experimental design. An online survey assembly module generates survey templates used by a data collection and sampling unit to display treatments to survey respondents. A model generation module analysis the collected data, and a model explorer module enables exploration of results. The system has the advantage of making choice modelling accessible to a wider range of users, and enables considerable freedom and scope to investigate problems of specific interest.

Abstract: Mechanisms for predicting a remaining useful life of a cutter head of a milling machine that includes a plurality of flutes are disclosed. Features are extracted from reference data associated with a plurality of reference cutter heads. The reference data includes reference vibration data and reference wear data. At least two Neural Network predictive models are trained in parallel for predicting the remaining life of a new cutter head based upon the extracted features. Operational data associated with the new cutter head is obtained. The operational data includes operational vibration data and operational wear data. Features extracted from the operational data are input into an optimal predictive model of the at least two Neural Network predictive models. A remaining useful life of the new cutter head is estimated by the optimal predictive model.

Abstract: A disclosed example method involves generating a plurality of wavelet coefficient quantities. Each wavelet coefficient quantity is generated based on items represented by probabilistic data. Each wavelet coefficient quantity represents different ones of the items by multiplying corresponding wavelet vectors. The example method also involves determining an error measure associated with each of the plurality of wavelet coefficient quantities, and selecting at least one of the plurality of wavelet coefficient quantities based on its associated error measure. The method also involves displaying parameter information associated with the one of the plurality of wavelet coefficient quantities to represent the probabilistic data.

Abstract: One or more measurement signatures are derived from a knowledge base of casual biological facts, where a signature is a collection of measured node entities and their expected directions of change with respect to a reference node. The knowledge base may be a directed network of experimentally-observed casual relationships among biological entities and processes, and a reference node represents a perturbation. A degree of activation of a signature is then assessed by scoring one or more “differential” data sets against the signature to compute an amplitude score. The amplitude score quantifies fold-changes of measurements in the signature. In one particular embodiment, the amplitude score is a weighted average of adjusted log-fold changes of measured node entities in the signature, wherein an adjustment applied to the log-fold changes is based on their expected direction of change. In an alternative embodiment, the amplitude score is based on quantity effects.