Abstract: In an embodiment, information for use in identifying a plurality of sub-solvers may be acquired. The plurality of sub-solvers may be used in a first attempt to find at least one solution to a problem that may be defined in the acquired information. At least two of the sub-solvers in the plurality of sub-solvers may be of different sub-solver types. The sub-solvers may be identified based on the acquired information. One or more starting points for the identified sub-solvers may be identified and transferred to the identified sub-solvers. One or more outputs, that indicate one or more results associated with the first attempt to find at least one solution to the problem, may be acquired from the identified sub-solvers. One or more sub-solvers may be identified, based on the acquired one or more outputs, for use in a second attempt to find at least one solution to the problem.

Abstract: Certain aspects of the present disclosure support techniques for unsupervised neural replay, learning refinement, association and memory transfer.

Abstract: A method and system for supporting a clinical diagnosis is provided, the method including the steps of representing a patient by a plurality of initial symptoms, the symptoms including characteristics of the patient; determining, by querying and reasoning in a disease-symptom knowledge model, at least one likely disease for each of the plurality of initial symptoms; mapping the plurality of initial symptoms onto a set of said likely diseases; determining for each disease of said set of likely diseases a plurality of associated symptoms, the associated symptoms being associated to a respective disease of said set of likely diseases in said disease-symptom knowledge model; categorizing each of the plurality of associated symptoms into disjoint categories by mapping associated symptoms with initial symptoms; and representing likely diseases in the context of said categories of associated symptoms.

Abstract: An information processing apparatus configured to create a schedule to be presented to a user includes an estimation unit and a creation unit. The estimation unit is configured to estimate whether or not the user acts in accordance with a first schedule including a task to do for accomplishing a preset aim. The creation unit is configured to create, when estimated that the user does not act in accordance with the first schedule, a new second schedule for accomplishing the aim from a state of the user who acts without following the first schedule.

Abstract: A pattern matching accelerator (PMA) for assisting software threads to find the presence and location of strings in an input data stream that match a given pattern. The patterns are defined using regular expressions that are compiled into a data structure comprised of rules subsequently processed by the PMA. The patterns to be searched in the input stream are defined by the user as a set of regular expressions. The patterns to be searched are grouped in pattern context sets. The sets of regular expressions which define the pattern context sets are compiled to generate a rules structure used by the PMA hardware. The rules are compiled before search run time and stored in main memory, in rule cache memory within the PMA or a combination thereof. For each input character, the PMA executes the search and returns the search results.

Abstract: A system for evaluating the threat posed by sensed targets includes sources of predetermined threat hypotheses and doctrinal information, and a Choquet threat discernment processor to identify a threat level represented by each target. A threshold arrangement is coupled evaluates the threat level, and deems those threat levels above the threshold to be suitable for the taking of countermeasures.

Abstract: An event-driven neural network includes a plurality of interconnected core circuits is provided. Each core circuit includes an electronic synapse array has multiple digital synapses interconnecting a plurality of digital electronic neurons. A synapse interconnects an axon of a pre-synaptic neuron with a dendrite of a post-synaptic neuron. A neuron integrates input spikes and generates a spike event in response to the integrated input spikes exceeding a threshold. Each core circuit also has a scheduler that receives a spike event and delivers the spike event to a selected axon in the synapse array based on a schedule for deterministic event delivery.

Abstract: An apparatus, system, method, and computer program product are disclosed for a predictive analytics factory. A receiver module is configured to receive training data. A function generator module is configured to determine a plurality of learned functions from multiple classes based on the training data. A predictive compiler module is configured to form a predictive ensemble comprising a subset of learned functions from the plurality of learned functions. The subset of learned functions is from at least two of the multiple classes.

Abstract: A system generates a consumer decision tree (“CDT”). The system receives customer purchasing data that includes transactions of a plurality of products each having at least one product attribute. For a product category, the system identifies a plurality of similar products from the purchasing data and one or more attributes corresponding to each similar product. The system assigns the product category as a current level of the CDT, and determines a most significant attribute of the plurality of attributes for the current level. The system forms a next level of the CDT by dividing the most significant attribute into a plurality of sub-sections, where each sub-section corresponds to an attribute value of the most significant attribute. The system then forms a next level of the CDT for each sub-section until a terminal node is identified.

Abstract: A system and method provides video recommendations for a target video in a video sharing environment. The system selects one or more videos that are on one or more video playlists together with the target video. The video co-occurrence data of the target video associates the target video and another video on one or more same video playlists and frequency of the target video and another video on the video playlists is computed. Based on the video co-occurrence data of the target video, one or more co-occurrence videos are selected and ranked based on the video co-occurrence data of the target video. The system selects one or more videos from the co-occurrence videos as video recommendations for the target video.

Abstract: The present invention provides a device and method for multiclass object detection, wherein the detection device includes: an input unit configured to input data to be detected; and a joint classifier within which a plurality of strong classifiers capable of processing multiclass object data are included, wherein each of the strong classifiers is acquired by adding a set of weak classifiers together, and each weak classifiers performs a weak classification for the data to be detected by using a feature. A list of shared features is included within the joint classifier, and each feature within the list is shared by one or more weak classifiers belonging to different strong classifiers respectively; and the weak classifiers, which use a same feature and belong to different strong classifiers respectively, have different parameter values from one another.

Abstract: A knowledge base system (1000) includes: a storage unit storing a knowledge base; and an operation unit (1070) performing a logic operation on the stored knowledge base. The knowledge base includes an entity identifier identifying an entity and one or more attributes of the entity associated with the entity identifier of the entity. Each attribute includes: an attribute identifier identifying the attribute; and at least one of feature data that is one or more pieces of data representing the attribute and is associated with the attribute identifier, and identification data that is data associated with a word representing the attribute and is associated with the attribute identifier. The entity identifier is not a word representing the entity, and is made of a symbol having no meaning per se. The attribute identifier is not the word representing the attribute, and is made of a symbol having no meaning per se.

Abstract: A pattern matching accelerator (PMA) for assisting software threads to find the presence and location of strings in an input data stream that match a given pattern. The patterns are defined using regular expressions that are compiled into a data structure comprised of rules subsequently processed by the PMA. The patterns to be searched in the input stream are defined by the user as a set of regular expressions. The patterns to be searched are grouped in pattern context sets. The sets of regular expressions which define the pattern context sets are compiled to generate a rules structure used by the PMA hardware. The rules are compiled before search run time and stored in main memory, in rule cache memory within the PMA or a combination thereof. For each input character, the PMA executes the search and returns the search results.

Abstract: A system and method for updating and correcting facts that receives proposed values for facts from users and determines a consensus value for the fact based on a distribution of the probabilities that the proposed values are the correct value for the fact wherein the probability that the proposed value is the correct value for the fact is based on a score indicative of the probability that the user proposing the value proposes accurate values.

Abstract: The present invention relates to an apparatus for automatic adjustment of a treatment of a target person to be treated based on calculated recovery prediction data for predicting a change of a sensory function of said target person in response to said treatment.

Abstract: A method, system, and device for determining client-based user behavioral analytics includes monitoring for a predetermined behavioral event on a computing device. The predetermined behavioral event may be embodied as any event initiated by the user on the computing device such as the purchase of a product, selection of a web link, navigation to a website, etc. In response to an occurrence of the predetermined behavioral event, an affinity metric and an avidity metric are determined based on a frequency of the occurrences of the predetermined behavioral event. A behavioral index for the user is determined based on the affinity metric and the avidity metric. Additionally, in response to receiving a request for the behavioral index, the computing device may transmit the behavioral index to a content provider server or other remote computer and receive content from the content provider, which has been selected based on the user's behavioral index.

Abstract: In one embodiment a method to create a system to manage documents with sensitive or classified content comprises extracting a list of text features enabling interaction with the user developing the system to create a rule-based classifier based on the list of text features and one or more synonymous features, applying the rule-based classifier to one or more selected documents to tag a set of documents with the sensitive or classified information they contain, training a statistical text classifier using the tagged documents generated as a training set, applying the trained statistical text classifier to the training set, and reapplying the refined rule-based classifier to the one or more documents to tag a set of documents with the sensitive or classified information they contain. Other embodiments may be described.

Abstract: User input on a computing device can be intelligently predicted using one or more learning algorithms. When user text input is received, an input repository comprising a plurality of text items is accessed. The plurality of text items includes a plurality of user-specific text items, which are classified according to a probabilistic model. One or more input predictions are inferred by applying the probabilistic model to the user text input. A suggested text input is presented using an output element of the computing device. The suggested text input is based on the user text input and one or more text items from the input repository. Additional input is received which overrides the suggested text. Any text associated with the user override is then classified within the probabilistic model, thereby updating the input repository based on the user override.

Abstract: Knowledge corroboration is described. In an embodiment many judges provide answers to many questions so that at least one answer is provided to each question and at least some of the questions have answers from more than one judge. In an example a probabilistic learning system takes features describing the judges or the questions or both and uses those features to learn an expertise of each judge. For example, the probabilistic learning system has a graphical assessment component which aggregates the answers in a manner which takes into account the learnt expertise in order to determine enhanced answers. In an example the enhanced answers are used for knowledge base clean-up or web-page classification and the learnt expertise is used to select judges for future questions. In an example the probabilistic learning system has a logical component that propagates answers according to logical relations between the questions.

Abstract: The present invention discloses a method for predicting the melt index and density of the polymer in terms of the operating conditions in the reactor and vice-versa, to select the operating conditions necessary to obtain the desired product specifications.