Abstract: When using Web intelligence (“Webint”) to collect information regarding a target social network user, one of the most valuable pieces of information is the target user's List-Of-Friends (LOF). In some cases, however, the LOF of the target user is not accessible in his profile. Herein are described methods and systems for identifying the LOF of a target user. An analysis system crawls the profiles of social network users, other than the target user, and reconstructs the LOF of the target user from the crawled profiles.

Abstract: In one embodiment, techniques are shown and described relating to a point-to-multipoint communication infrastructure for expert-based knowledge feed-back using learning machines. A learning machine may communicate an expert discovery request into a network to discover one or more experts, and then receive from the one or more experts, one or more expert discovery responses. Based on the one or more received expert discovery responses, the learning machine may then build a dynamic multicast tree of experts to assist the learning machine in a computer network.

Abstract: A method for managing and automating user customization of a device based on observed user behavior is disclosed. First, the method collects data on the user's activities on a device for a period of time. Second, the method learns about the user's behavior for routine repetitive operations by analyzing the user's activities data. Third, the method generates automation settings of the device based on the user's behavior for routine repetitive and predictive operations, and then presents the automation settings of the device to the user for customization of the device. These automation settings help to make the device operate more efficiently and more conveniently for the user, because they help perform the user's own routine repetitive operations.

Abstract: A neural network includes a plurality of inputs for receiving input signals, and synapses connected to the inputs and having corrective weights established by a memory element that retains a respective weight value. The network additionally includes distributors. Each distributor is connected to one of the inputs for receiving the respective input signal and selects one or more corrective weights in correlation with the input value. The network also includes neurons. Each neuron has an output connected with at least one of the inputs via one synapse and generates a neuron sum by summing corrective weights selected from each synapse connected to the respective neuron. The output of each neuron provides the respective neuron sum to establish operational output signal of the network. A method of operating a neural network includes processing data thereby and using modified corrective weight values established by a separate analogous neural network during training thereof.

Abstract: Automatic recognition and presentation of insights of data is provided through analysis of overall data to infer locations of a user's data. Statistical, heuristic, and comparable analysis on the user's data sets is used to determine insights such as trends, correlations, outliers, comparisons, and patterns. The insights are then presented to the user through automatically optimized visualizations (highlighting determined insights), emphasis on presented raw data, data formatting suggestions, and similar ones with the capability to explore further.

Abstract: Aspects of the disclosure generally relate to computing devices and may be generally directed to devices, systems, methods, and/or applications for learning conversations among two or more conversation participants, storing this knowledge in a knowledgebase (i.e. neural network, graph, sequences, etc.), and enabling a user to simulate a conversation with an artificially intelligent conversation participant.

Abstract: Methods, systems, and products adapt recommender systems with pairwise feedback. A pairwise question is posed to a user. A response is received that selects a preference for a pair of items in the pairwise question. A latent factor model is adapted to incorporate the response, and an item is recommended to the user based on the response.

Abstract: A method to solve large scale linear SVM that is efficient in terms of computation, data storage and communication requirements. The approach works efficiently over very large datasets, and it does not require any master node to keep any examples in its memory. The algorithm assumes that the dataset is partitioned over several nodes on a cluster, and it performs “distributed block minimization” to achieve the desired results. Using the described approach, the communication complexity of the algorithm is independent of the number of training examples.

Abstract: A computer-implemented content suggestion engine provides content suggestions to a requesting user based on information about content items that other users may have independently categorized or organized into folders within a content repository. Embodiments of the method comprise a content repository having a plurality of content items, where each content item is associated with one or more user-created folders. Embodiments further comprise receiving, via a network, a suggestion request for suggested content, where the suggestion request identifies a first content item for which suggestions are sought. Other content items in the content repository are then identified as potential suggestions based on the application of a formal relationship between the first content item and the potential suggested content items. One or more of the potential suggested content items may then be provided in response to the suggestion request via the network.

Abstract: A method for planning trips to transport passengers on the basis of a preferably statistical predictive model, in particular to plan capacities, optimize the utilization of vehicle fleets, determine the routes to be taken, etc., preferably in short-distance passenger traffic, wherein the predictive model takes into account, using parameters, characteristic passenger patterns over the course of a day, week, and/or year, is characterized in that the predictive model additionally uses weather-specific parameters.

Abstract: A method, system, and computer program product for resource management are described. The method includes selecting trouble regions within the service area, generating clustered regions, and training a trouble forecast model for the trouble regions for each type of damage, the training for each trouble region using training data from every trouble region within the clustered region associated with the trouble region. The method also includes applying the trouble forecast model for each trouble region within the service area for each type of damage, determining a trouble forecast for the service area for each type of damage based on the trouble forecast for each of the trouble regions within the service area, and determining a job forecast for the service area based on the trouble forecast for the service area, wherein the managing resources is based on the job forecast for the service area.

Abstract: A method for generating an operational rule associated with a building management system includes identifying, with a processing device, a first pattern associated with a series of operational observations corresponding to a property of the building management system, correlating a first contextual attribute with the first pattern, and deriving the operational rule at least in part based on the first pattern and the first contextual attribute.

Abstract: Monitoring system and method for use with diabetic treatment management. The system comprises: a communication interface configured to permit access to stored raw log data, obtained over a certain time, being indicative of glucose measurements, meals consumed and insulin delivery; and a control unit comprising an unsupervised learning controller configured to receive and process said raw log data and determine at least one global insulin pump setting of basal rate, correction factor, carbohydrate ratio and insulin activity curve parameters. The system may comprise a processing unit comprising a first processor for processing measured data indicative of blood glucose level and generating first processed data, a second processor comprising at least one fuzzy logic module which receives input parameters corresponding to the measured data, the first processed data and a reference data, and processes the data to produce a qualitative output parameter to determine whether any treatment parameter should be modified.

Abstract: A system monitors a network or web application provided by one or more distributed applications and provides data for each and every method instance in an efficient low-cost manner. Agents may monitor the performance of the distributed application by the web services and report monitoring data as runtime data to the remote server, for example a controller. The controller may analyze the data to identify one or more performance issues or “hot spot” methods based on current or past performance, functionality, content, or business relevancy. Instructions and/or configuration information may be transmitted by the controller to the agents that correspond to a particular business transaction portion associated with a hot spot. The portions are then monitored to collect data associated with the hot spot and the hot spot data is reported back to the controller.

Abstract: A method for generating an operational rule associated with a building management system includes identifying, with a processing device, a first pattern associated with a series of operational observations corresponding to a property of the building management system, correlating a first contextual attribute with the first pattern, and deriving the operational rule at least in part based on the first pattern and the first contextual attribute.

Abstract: An approach is presented for identifying related problem tickets in an information technology (IT) environment. A pattern of actions included in interactions with a computer program is determined to be effective at proactively preventing a problem in the IT environment based on a frequency at which user(s) performed the interactions which perform text and statistical analyses of content of historical problem tickets. A script based on the pattern of actions is generated. A root cause of the problem is determined based on the text and statistical analyses. Responsive to a receipt of a new problem ticket, the script is executed to automatically perform the pattern of actions. The new problem ticket is classified as being in a group of problem tickets which are related to the problem and included in the historical problem tickets. The new problem ticket is determined to specify the problem which has the root cause.

Abstract: A medical digital expert system to predict a patient's response to a variety of treatments (using pre-treatment information) is described. The system utilizes data fusion, advanced signal/information processing and machine learning/inference methodologies and technologies to integrate and explore diverse sets of attributes, parameters and information that are available to select the optimal treatment choice for an individual or for a subset of individuals suffering from any illness or disease including psychiatric, mental or neurological disorders and illnesses. The methodology and system can also be used to determine or confirm medical diagnosis, estimate the level, index, severity or critical medical parameters of the illness or condition, or provide a list of likely diagnoses for an individual suffering/experiencing any illness, disorder or condition.

Abstract: In one embodiment, variables maintained by each of a plurality of Learning Machines (LMs) are determined. The LMs are hosted on a plurality of Field Area Routers (FARs) in a network, and the variables are sharable between the FARs. A plurality of correlation values defining a correlation between the variables is calculated. Then, a cluster of FARs is computed based on the plurality of correlation values, such that the clustered FARs are associated with correlated variables, and the cluster allows the clustered FARs to share their respective variables.

Abstract: Disclosed are various embodiments that provide a mixture model approach to network forecasting. Network traffic models are generated for multiple host types. Weights are determined for the network traffic models. A network forecast is generated based at least in part on a hardware footprint forecast and on the network traffic models as weighted by the determined weights.

Abstract: Automatic recognition and presentation of insights of data is provided through analysis of overall data to infer locations of a user's data. Statistical, heuristic, and comparable analysis on the user's data sets is used to determine insights such as trends, correlations, outliers, comparisons, and patterns. The insights are then presented to the user through automatically optimized visualizations (highlighting determined insights), emphasis on presented raw data, data formatting suggestions, and similar ones with the capability to explore further.