Abstract: A computer-enabled system, method, and medium provides intellectual property analyses, for example, patent claim charts, respective to the analyzed intellectual property and a target product or other intellectual property. Analyses are stored to enable searching/reporting across multiple analyses. Units of the analysis are associated with context, inherited, e.g., from the intellectual property document's assignment to a relative role within the organizational hierarchy; and associated with a context derived from the analysis itself. The analysis and respective documents and/or targets of the analysis can be searched/retrieved/analyzed from the hierarchical analysis, the context analysis, and/or the content of the analysis. Each analysis need not be stored as a separate document. The representation of the analysis may by static or dynamic.

Abstract: A method for managing synapse plasticity in a neural network includes converting a first set of synapses from a plastic synapse type to a fixed synapse type. The method may also include converting a second set of synapses from the fixed synapse type to the plastic synapse type.

Abstract: A computer-enabled system, method, and medium is provided to correlate intellectual property analysis, for example, patent claim charts, with respect to the analyzed intellectual property and a target product or other intellectual property. Analysis are stored in a manner that enables searching across multiple analysis, and creating reports over multiple analysis. Units of the analysis are associated with a context, inherited, e.g., from the intellectual property document's assignment to a relative role within the organizational hierarchy; and associated with a context derived from the analysis itself. The analysis and respective documents and/or targets of the analysis can be searched/retrieved/analyzed from the hierarchical analysis, the context analysis, and/or the content of the analysis. This obviates the need to store each analysis as a separate document. The representation of the analysis may be static or dynamic.

Abstract: Determining geospatial patterns from device data collected from a plurality of computing devices. The devices represent, for example, a plurality of sources providing the device data. The device data describes the computing devices and/or environments thereof. Some embodiments present the determined patterns to users for editing, update maps with the edited patterns, and distribute the maps to the users. The maps are stored to create a searchable map library.

Abstract: An apparatus and a method are provided for learning a program with a large number of parameters. In one embodiment, a method not only distorts the input values, but also distorts some of the parameters in the program model. Such an approach not only forces the learned program to acquire parameter values to predict missing or desired data, but also to correct errors in the input data and the program parameters themselves, thereby rendering the learned program more resilient to overfitting and falling into local optima.

Abstract: An apparatus includes an execution module, a determination module, and a generation module. In one embodiment, the execution module parses a business rule as input into a meta rule on a rule engine. The meta rule includes a first expression defining one or more style conditions for business rules. The business rule includes a second expression defining logic for an entity. The determination module, in one embodiment, determines that a business rule violates a style condition defined by the meta rule. The business rule and the meta rule conform to a common business rule syntax. The generation module, in one embodiment, generates a notification in response to determining that the business rule violates the style condition of the meta rule.

Abstract: Deployment pattern matching is implemented by accessing a target computing environment model that captures environment modeling parameters relating to resources and resource-resource relationships of a corresponding computing environment and expressing the target computing environment model as a model graph defined by target resource elements and resource-to-resource relationship links. Deployment pattern matching is further implemented by accessing a realization pattern that captures deployment parameters relating to resources and resource-resource relationships of a deployment of interest and expressing the realization pattern as a pattern graph defined by conceptual resource elements and constraints arranged by resource-to-resource relationship links and constraint links.

Abstract: The present invention relates to a method and apparatus for tailoring the output of an intelligent automated assistant. One embodiment of a method for conducting an interaction with a human user includes collecting data about the user using a multimodal set of sensors positioned in a vicinity of the user, making a set of inferences about the user in accordance with the data, and tailoring an output to be delivered to the user in accordance with the set of inferences.

Abstract: A system and computer-implemented method for determining a threat level for one or more individuals includes accessing a data structure to obtain aggregated data stored therein, wherein the aggregated data comprises at least one of communication history data or transaction history data for one or more individuals. One or more predetermined metrics are applied to the obtained aggregated data, to determine threat level information for the one or more individuals. The determined threat level information is provided for display.

Abstract: A method for conducting search-by-content is provided. The method includes responsive to an input multimedia content item provided to a user device, checking if the input multimedia content item matches at least one concept of a plurality of concepts cached in the user device; retrieving characteristics set for a user of the user device; performing a search, using the at least one matching concept, for multimedia content items similar to the input multimedia content item; determining which of the search results are of interest to the user based on the characteristics set for the user; and saving results that are of interest to the user in the user device, wherein the saved results include multimedia content items.

Abstract: A method for decision reasoning, the method comprising using at least one hardware processor to: provide a database comprising decisions, questions and reasons; receive, from a user, a selection of a decision being part of said decisions; retrieve, from said database, relevant questions out of said questions, wherein said relevant questions are associated, within said database, with said decision received from the user; receive, from the user, answers to at least some of said relevant questions; process said answers so as to retrieve, from said database, one or more relevant reasons out of said reasons; and display said one or more relevant reasons to the user.

Abstract: Transfer learning is the task of leveraging the information from labeled examples in some domains to predict the labels for examples in another domain. It finds abundant practical applications, such as sentiment prediction, image classification and network intrusion detection. A graph-based transfer learning framework propagates label information from a source domain to a target domain via the example-feature-example tripartite graph, and puts more emphasis on the labeled examples from the target domain via the example-example bipartite graph. An iterative algorithm renders the framework scalable to large-scale applications. The framework propagates the label information to both features irrelevant to the source domain and unlabeled examples in the target domain via common features in a principled way.

Abstract: Provided are techniques for dynamic mathematical validation using data mining. As text is being received, a mathematical statement is identified in the text based on context of the text. A mathematical solution to the mathematical statement is identified in the text based on the context of the text. It is determined that the mathematical solution is incorrect using data mining. In response to determining that auto-correction is to be performed, the mathematical solution is corrected.

Abstract: Provided are techniques for dynamic mathematical validation using data mining. As text is being received, a mathematical statement is identified in the text based on context of the text. A mathematical solution to the mathematical statement is identified in the text based on the context of the text. It is determined that the mathematical solution is incorrect using data mining. In response to determining that auto-correction is to be performed, the mathematical solution is corrected.

Abstract: Described is a system for automated collaborative behavior analysis using temporal motifs. The system receives an input documents and change log files of a collaborative media, where the documents are continuously edited by multiple authors and where edits are recorded in the change log files, such as Wikipedia. A type of editing behavior by the authors of a given document is identified, and the edits made to the document are analyzed. The system reports how the authors interacted in a collaboration process, resulting in a set of reported author interactions. From the set of reported author interactions, a set of author interactions that are most and least significant in the collaboration process are identified. Then, based on the set of identified author interactions, future effects on documents of the collaborative media are estimated.

Abstract: A learning health system and associated methods are provided. Biochemical assays are conducted at scheduled intervals on blood samples taken from an individual to provide, for each of a plurality of biochemical parameters, a time series of values representing the individual. Clinical parameters associated with the individual are extracted from a knowledge base. Genomic parameters are determined for the individual. An expected time series is calculated for each of a plural subset of the plurality of biochemical parameters from at least the clinical parameters and the genomic parameters. For each of the plural subset of biochemical parameters, the time series of values representing the individual is compared to the calculated expected time series to determine a likelihood of each of a plurality of conditions for the individual. The likelihood of at least one of the plurality of conditions is communicated to a user.

Abstract: A system correlates intellectual property analyses, for example, patent claim charts, with respect to analyzed intellectual property and a target product or other intellectual property. Analyses are stored to enable searching and/or creating reports over multiple analyses. Units of the analysis are associated with a context, inherited, e.g., from the intellectual property document's assignment to a relative role within organizational hierarchy; and associated with a context derived from the analysis itself. The analysis and respective documents and/or targets of the analysis can be searched/retrieved/analyzed from the hierarchical analysis, the context analysis, and/or the content of the analysis. This obviates the need to store each analysis as a separate document. The target or annotations may be visually represented by an item such as a thumbnail or hyperlink, and the system automatically associates the item with the appropriate application program.

Abstract: A system correlates intellectual property analyzes, for example, patent claim charts, with respect to analyzed intellectual property and a target product or other intellectual property. Analyzes are stored to enable searching and/or creating reports over multiple analyzes. Units of the analysis are associated with a context, inherited, e.g., from the intellectual property document's assignment to a relative role within organizational hierarchy; and associated with a context derived from the analysis itself. The analysis and respective documents and/or targets of the analysis can be searched/retrieved/analyzed from the hierarchical analysis, the context analysis, and/or the content of the analysis. This obviates the need to store each analysis as a separate document. The target or annotations may be visually represented by an item such as a thumbnail or hyperlink, and the system automatically associates the item with the appropriate application program.

Abstract: Architecture introduces a new pattern operator referred to as called an augmented transition network (ATN), which is a streaming adaptation of non-reentrant, fixed-state ATNs for dynamic patterns. Additional user-defined information is associated with automaton states and is accessible to transitions during execution. ATNs are created that directly model complex pattern continuous queries with arbitrary cycles in a transition graph. The architecture can express the desire to ignore some events during pattern detection, and can also detect the absence of data as part of a pattern. The architecture facilitates efficient support for negation, ignorable events, and state cleanup based on predicate punctuations.

Abstract: An adaptive probabilistic computer-controlled method and system determines computer-controlled actions that are expected to reduce uncertainties that are embodied as probabilities and then updates the probabilities in accordance with the results of the computer-controlled actions. The updated probabilities inform the determination of subsequent computer-controlled actions. Expected values of information may also be applied in determining the subsequent computer-controlled actions. The computer-controlled actions may comprise analysis of content and generating recommendations that are delivered to users, and inferences from the analysis of content and usage behaviors may inform the updating of the probabilities. Statistical learning functions and/or neural networks may be applied in determining the computer-controlled actions.