Abstract: The present invention is directed towards methods and computer readable media for annotating and ranking user reviews on social review systems with inferred analytics. A reference framework is provided by creating context according to previous activity, bias, or background information of a given reviewer. The method of the present invention comprises receiving a first query identifying a given content item, generating a collection of content items based on one or more identical objective attributes associated with the given content item, identifying one or more subjective attributes associated with a given item in the collection of items, and providing a reference framework to interpret the subjective attributes associated with each item in the collection.

Abstract: It is disclosed to determine whether information useable for a generating/updating process that comprises generating and/or updating at least one model for a coverage area of a communication node shall be discarded or made available to said generating/updating process.

Abstract: A method of generating a summary review of an entity from a set of reviews includes generating a distribution and determining a polarity of the distribution associated with a plurality of aspect ratings based on the set of reviews. The set of reviews are associated with the entity, and the plurality of aspect ratings are associated with an aspect, or feature, of the entity. The method includes selecting an opinion correlated with the polarity from the set of reviews, and generating the summary review, the summary review comprising: a summary statement based on the distribution and the polarity; and the opinion. An apparatus and computer-readable device are also disclosed.

Abstract: Techniques are provided for automatically structuring free form heterogeneous data. In one aspect of the invention, the techniques include obtaining free form heterogeneous data, segmenting the free form heterogeneous data into one or more units, automatically labeling the one or more units based on one or more machine learning techniques, wherein each unit is associated with a label indicating an information type, and structuring the one or more labeled units in a format to facilitate one or more operations that use at least a portion of the labeled units, e.g., information technology (IT) operations.

Abstract: In certain implementations, a system may receive attribute data corresponding to attributes of a plurality of users and to one or more venues for which the plurality of users has an affinity. A user personality matrix may be calculated for one or more of the plurality of users based on interrelational nodal link strengths between the one or more users and the venues. The user personality matrices may be merged to calculate a combined personality matrix representing a unified taste profile for the one or more users. A candidate list of venues having the highest link strength with the combined personality matrix may be determined. One or more recommended venues from the candidate list of venues that have the strongest links to the combined personality matrix may be determined, and recommendation data corresponding to the recommended venues may be output.

Abstract: Devices, systems and methods for operating a memory device facilitating a neural network in a memory device are disclosed. In at least one embodiment, the memory device is operated having a feed-ward neural network operating scheme. In at least one other embodiment, memory cells are operated to emulate a number of neural models to facilitate one or more neural network operating characteristics in the memory device.

Abstract: Embodiments of the invention relate to mapping neural dynamics of a neural model on to a lookup table. One embodiment comprises defining a phase plane for a neural model. The phase plane represents neural dynamics of the neural model. The phase plane is coarsely sampled to obtain state transition information for multiple neuronal states. The state transition information is mapped on to a lookup table.

Abstract: Generating test data includes: reading values occurring in at least one field of multiple records from a data source; storing profile information including statistics characterizing the values; generating a model of a probability distribution for the field based on the statistics; generating multiple test data values using the generated model such that a frequency at which a given value occurs in the test data values corresponds to a probability assigned to that given value by the model; and storing a collection of test data including the test data values in a data storage system.

Abstract: Techniques, systems, and articles of manufacture for determining related data points from multi-modal inputs. A method includes collecting multiple items of multi-modal data comprising at least one dimension from multiple data sources, wherein said at least one dimension comprises a geographic dimension, a temporal dimension and/or an event-related dimension, determining a window of relevance for each of the multiple items of multi-modal data with respect to the at least one dimension, and identifying two or more of the multiple items of multi-modal data as related, by determining an overlap of the window of relevance corresponding to each of the two or more items of multi-modal data with respect to the at least one dimension.

Abstract: The present invention provides a technique for building natural language parsers by implementing a country and/or jurisdiction specific set of training data that is automatically converted during a build phase to a respective predictive model, i.e., an automated country specific natural language parser. The predictive model can be used without the training data to quantify any input address. This model may be included as part of a larger Geographic Information System (GIS) data-set or as a stand alone quantifier. The build phase may also be run on demand and the resultant predictive model kept in temporary storage for immediate use.

Abstract: The illustrative embodiments provide for a computer implemented method, computer readable medium, and data processing system for adjusting a perceived image seen through an optical observation device. The azimuth-elevation-rotation of the optical observation device is measured relative to an observer. The field of view observed through the observation device appears with at least one of rotated and inverted optical translation relative to observation of the object with an unaided eye of the observer. Based on the celestial coordinate system inherent in the design of the mounting of the optical observation device, moving optical observation device in the optical translation direction, wherein the field of view moves in the optical view direction, and wherein the celestial coordinate system is selected from a group consisting of an equatorial coordinate system and an azimuth-elevation coordinate system.

Abstract: Systems and methods are described herein for analyzing neural response data that can be assigned to multiple classes. The systems and methods begin with a set of training data from which optimal weight factors are derived. The derived weight factors are used in a classifier which is then applied to test data from test subjects. The classifier filters out the effects of less relevant data in the test data and provides a result in the form of probabilities associated with classes for the test data.

Abstract: Methods and systems for a complete vehicle ecosystem are provided. Specifically, sensor data, accumulated from one or more sensors of one or more vehicles, is compared to rules or standards. Based on the comparison, a system may generate and provide etiquette suggestions to the one or more vehicles to ensure those vehicles do not create a disruption in the flow of traffic. The one or more vehicles can receive the suggestions and provide the suggestions to a user. The user or the vehicle may decide to act on the suggestion.

Abstract: A base word to be a base, a compound word in which the base word becomes a modifiee, classification items to classify the compound word, and feature information about a feature that provides a clue to classify the compound word are acquired (S10, S11, S12, S13), the compound word containing the base word is distributed into the acquired classification item using a classification model generated in advance and the acquired feature information (S14, S15), base word related information containing a plurality of elements related to the base word is acquired based on the base word (S16), each of at least a portion of the elements contained in the acquired base word related information is classified into one of the classification items in accordance with a result of the classification (S17), and the classified base word related information (Web pages 40, 50, 51) is output (S18).

Abstract: A system and method of synchronizing recipes and bills of materials (BOM). An approved recipe is parameterized in a planning interface. A BOM is synchronized with the parameterized recipe. The BOM is then displayed in a graphical user interface to allow a user to modify by a resolve conflict present during synchronization.

Abstract: A state machine engine having a program buffer. The program buffer is configured to receive configuration data via a bus interface for configuring a state machine lattice. The state machine engine also includes a repair map buffer configured to provide repair map data to an external device via the bus interface. The state machine lattice includes multiple programmable elements. Each programmable element includes multiple memory cells configured to analyze data and to output a result of the analysis.

Abstract: An approach for seismic data analysis is provided. In accordance with various embodiments, the active learning approaches are employed in conjunction with an analysis algorithm that is used to process the seismic data. Algorithms that may employ such active learning include, but are not limited to, ranking algorithms and classification algorithms.

Abstract: Various methods and systems are provided for classification using correntropy. In one embodiment, a classifying device includes a processing unit and memory storing instructions in modules that when executed by the processing unit cause the classifying device to adaptively classify a data value using a correntropy loss function. In another embodiment, a method includes adjusting a weight of a classifier based at least in part on a change in a correntropy loss function signal and classifying a data value using the classifier. In another embodiment, a method includes classifying a data value by predicting a label for the data value using a discriminant function, determining a correntopy statistical similarity between the predicted label and an actual label based at least in part on a correntropy loss function, and minimizing an expected risk associated with the predicted label based at least in part on a correntropy statistical similarity.

Abstract: A system for estimating long term characteristics of a battery includes a learning data input unit for receiving initial characteristic learning data and long term characteristic learning data of a battery to be a learning object; a measurement data input unit for receiving initial characteristic measurement data of a battery to be an object for estimation of long term characteristics; and an artificial neural network operation unit for receiving the initial characteristic learning data and the long term characteristic learning data from the learning data input unit to allow learning of an artificial neural network, receiving the initial characteristic measurement data from the measurement data input unit and applying the learned artificial neural network thereto, and thus calculating long term characteristic estimation data from the initial characteristic measurement data of the battery and outputting the long term characteristic estimation data.

Abstract: Evaluating candidate answers to questions in a target knowledge domain, including: identifying, by a question answering module, a plurality of evidence items in the target knowledge domain; identifying, by the question answering module, a plurality of answers to questions in the target knowledge domain; determining, by the question answering module, associations between each evidence item and one or more of the answers; receiving, by the question answering module, a question; receiving, by the question answering module, values for the one or more evidence items; and providing, by the question answering module, an answer to the question in dependence upon the associations between each evidence item and one or more of the answers and the values for the one or more evidence items.