Abstract: User interactions are categorized into predefined hierarchical categories by classifying user interactions, such as queries, during a user interaction session by labeling text data into predefined hierarchical categories, and building a scoring model. The scoring model is then executed on untagged user interaction data to classify the user interactions into either action-based or information-based interactions.

Abstract: Methods, systems and computer program products are provided for cross-media recommendation by store a plurality of taste profiles corresponding to a first domain and a plurality of media item vectors corresponding to a second domain. An evaluation taste profile in the first domain is applied to a plurality of models that have been generated based on relationship among the plurality of taste profiles and the plurality of media item vectors, and obtain a plurality of resulting codes corresponding to at least one of the plurality of media item vectors in the second domain.

Abstract: One aspect of the present disclosure relates to a system for providing a recommendation for a game based on a game-centric relationship graph. The relationship graph is a graph depicting relationships between game and game users. One or more recommended games may be determined by leveraging the relationship graph. For example, recommended games may be identified based on graph proximities from candidate game nodes to a target user node or a mathematical score calculated from weight metrics of relationship branches.

Abstract: An apparatus, a method, and a non-transitory computer readable storage medium thereof for recommending an electricity consumption behavior are provided. The apparatus is stored with an appliance efficiency value and an electricity-consuming parameter value for each of a plurality of users. The apparatus generates a plurality of first temporary values by multiplying each of the appliance efficiency values with each of the electricity-consuming parameters, generates a power saving matrix by subtracting each of the electricity-consuming parameters from each of the electricity-consuming parameters individually, generates a changing willingness matrix by the second temporary values, calculates a transform probability matrix by the power saving matrix and the changing willingness matrix, calculates an eigenvalue and an eigenvector of the transform probability matrix, and recommends an electricity consumption behavior according to the eigenvalue and the eigenvector.

Abstract: Self-learning and adaptive modeling is employed with respect to predictive analytics. A hierarchical model structure can be employed comprising a set of predictive models automatically built from accumulated data and distributed across multiple levels. For a given input type, a set of candidate models can be identified across varying levels of granularity, and a best model selected based on a comparison of performance metrics of the models. The best model can then be activated for use in making predictions. Of course, the best model can change based on most recent training performance results, since as more data becomes available more specific models can be developed.

Abstract: Particular embodiments may retrieve information associated with one or more nodes of a social graph from one or more data stores. A node may comprise a user node or a concept node. Each node may be connected by edges to other nodes of a social graph. A first user may be associated with a first user node of the social graph. Particular embodiments may detect that the first user is entering an input term. Predictive typeahead results may be provided as the first user enters the input term. The predictive typeahead results may be based on the input term. Each predictive typeahead result may include at least one image. Each predictive typeahead result may correspond to at least one node of the social graph.

Abstract: Systems and methods for understanding (imputing meaning to) multi modal data streams may be used in intelligent surveillance and allow a) real-time integration of streaming data from video, audio, infrared and other sensors; b) processing of the results of such integration to obtain understanding of the situation as it unfolds; c) assessing the level of threat inherent in the situation; and d) generating of warning advisories delivered to appropriate recipients as necessary for mitigating the threat. The system generates understanding of the system by creating and manipulating models of the situation as it unfolds. The creation and manipulation involve “neuronal packets” formed in mutually constraining associative networks of four basic types. The process is thermodynamically driven, striving to produce a minimal number of maximally stable models. Obtaining such models is experienced as grasping, or understanding the input stream (objects, their relations and the flow of changes).

Abstract: A mechanism is provided in a data processing system for predicting and enhancing ingestion time for a set of input documents. The mechanism receives a set of documents to be added to a corpus of the data processing system. The mechanism records document features of each document within the set of documents using an annotation engine within the data processing system. The mechanism predicts an ingestion time for each document within the set of documents based on the document characteristics and a machine learning model. The mechanism assigns the set of documents to data processing system resources to be processed based on the predicted ingestion time for each document.

Abstract: In an aspect, in general, a programmable computation device performs computations of an inference task specified by a plurality of variables and a plurality of factors, each factor being associated with a subset of the variables. The device includes one or more processing elements. Each processing element includes a first storage for a definition of a factor, a second storage for data associated with the inputs and/or outputs of at least some of the computations, and one or more computation units coupled to the first storage and the second storage for performing a succession of parts of the at least some of the computations that are associated with a factor, the succession of parts defined by data in the storage for the definition of the factor.

Abstract: A method for coordinate transformation in a spiking neural network includes encoding a first positional representation as phase information in the spiking neural network. The method also includes shifting the phase information to modify the first positional representation into a second positional representation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for reinforcement learning using confidence scores. One of the methods includes receiving a current observation; for each of multiple actions: determining a respective value function estimate that is an estimate of a return resulting from the agent performing the action in response to the current observation, determining a respective confidence score that is a measure of confidence that the respective value function estimate for the action is an accurate estimate of the return that will result from the agent performing the action in response to the current observation, adjusting the respective value function estimate for the action using the respective confidence score for the action to determine a respective adjusted value function estimate; and selecting an action to be performed by the agent in response to the current observation using the respective adjusted value function estimates.

Abstract: In accordance with embodiments, there are provided mechanisms and methods for messaging in an on-demand database service. These mechanisms and methods for messaging in an on-demand database service can enable embodiments to more flexibly message in on-demand database environments. The ability of embodiments to provide such feature may lead to enhanced messaging features which may be used for providing more effective ways of messaging in the context of on-demand databases.

Abstract: Measurement-only topological quantum computation using both projective and interferometrical measurement of topological charge is described. Various issues that would arise when realizing it in fractional quantum Hall systems are discussed.

Abstract: A Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system for inter-device communication is described. Information data from each neuromorphic chip is coded and modulated, on the basis of destination, into different channels. The parallel signals in different channels are sent serially using TDM to a central router. After signal grouping by a central switching controller, each group of signals may be delivered to corresponding transmitter in the central router for transmission to a corresponding receiver in the neuromorphic chip using TDM.

Abstract: A method and apparatus for managing configurations of computer resources in a datacenter is described. In one embodiment, a method comprises analyzing multiple configurations using rule information to produce an analysis result where each configuration in the multiple configurations defines a configuration of a resource that is managed by the data center, training a Bayesian classifier using the analysis result, and classifiying a second configuration using the trained Bayesian classifier.

Abstract: Various embodiments select features from a feature space. In one embodiment, a set of training samples and a set of test samples are received. The set of training samples includes a set of features and a class value. The set of test samples includes the set of features absent the class value. A relevancy with respect to the class value is determined for each of a plurality of unselected features based on the set of training samples. A redundancy with respect to one or more of the set of features is determined for each of the plurality of unselected features in the first set of features based on the set of training samples and the set of test samples. A set of features is selected from the plurality of unselected features based on the relevancy and the redundancy determined for each of the plurality of unselected features.

Abstract: In a method of answering questions and scoring answers, a title and at least one topical field are identified for a document. A field name and field content associated with the topical field is identified, and a title-oriented document is created by combining the title, the field name, and the field content associated with the topical field. For each title-oriented document, a term in the title is matched to previously established categories to produce a title concept identifier. The topical field is synthesized to produce a field concept identifier and a field content concept identifier. A question is received. The question topic term and the question content identifier are used to identify at least one question-matching relation instance. The title concept identifier of each question-matching relation instance is identified as a candidate answer to the question. Each candidate answer and a corresponding answer score is output.

Abstract: Methods and apparatus for piecewise linear neuron modeling and implementing artificial neurons in an artificial nervous system based on linearized neuron models. One example method for operating an artificial neuron generally includes determining that a first state of the artificial neuron is within a first region; determining a second state of the artificial neuron based at least in part on a first set of linear equations, wherein the first set of linear equations is based at least in part on a first set of parameters corresponding to the first region; determining that the second state of the artificial neuron is within a second region; and determining a third state of the artificial neuron based at least in part on a second set of linear equations, wherein the second set of linear equations is based at least in part on a second set of parameters corresponding to the second region.

Abstract: A system for predicting the thickness of a battery is disclosed. In one aspect, the battery thickness predicting system includes a learning data input unit for receiving data on a previously manufactured battery. The thickness predicting system further includes an object data input unit for receiving data on a battery whose thickness is to be predicted. The system further comprises a mechanical learning unit connected to the learning data input unit to obtain a predicting function based on learning factors input to the learning data input unit and to provide weight values to the learning factors, respectively. The system further includes a thickness predicting unit connected to the object data input unit and the mechanical learning unit and using the weight values provided by the mechanical learning unit in order to predict the thickness of the battery whose thickness is to be predicted.

Abstract: A method, system, and computer-readable storage medium are disclosed for accurately estimating the audience of digital content. A plurality of user interactions occurring on a digital device are received, wherein digital content is displayed on the digital device. Based on the plurality of user interactions, a total number of unique viewers of the digital content on the digital device is estimated.