1033results about "Non-linear system models" patented technology

A method, system and computer program product for generating a document representation are disclosed. The system includes a server and a client computer, and the method involves: receiving into memory a resource containing at least one sentence of text; producing a tree comprising tree elements indicating parts-of-speech and grammatical relations between the tree elements; producing semantic structures each having three tree elements to represent a simple clause (subject-predicate-object); and storing a semantic network of semantic structures and connections therebetween. The semantic network may be created from a user provided root concept. Output representations include concept maps, facts listings, text summaries, tag clouds, indices; and an annotated text. The system interactively modifies semantic networks in response to user feedback, and produces personal semantic networks and document use histories.

The user is allowed to automatically generate a program by using a visual programming method and a system adopting the method for automatically generating a program wherein an object selection means 8 is used for selecting a behavioral graphical object defining the behavior of a load connected thereto, a behavior selection means 9 is used for selecting the type of the behavior of the behavioral graphical object, a relevant object selection means 10 is used for selecting relevant graphical objects related to the behavior of the behavioral graphical object and a behavioral rule setting means 11 is used for setting behavioral rules of the behavioral graphical object whereas a behavioral characteristic selection unit 3509 is used for selecting a behavior of a behavioral graphical object selected by using a behavioral object selection unit 3508, behavioral condition setting unit 3510 is used for setting conditions for the behavior of the behavioral graphical object and a relevant object selection unit 3511 is used for defining a relation.

The present invention is directed to a computer automated method of selectively identifying a user specified behavior of a crowd. The method comprises receiving video data but can also include audio data and sensor data. The video data contains images a crowd. The video data is processed to extract hierarchical human and crowd features. The detected crowd features are processed to detect a selectable crowd behavior. The selected crowd behavior detected is specified by a configurable behavior rule. Human detection is provided by a hybrid human detector algorithm which can include Adaboost or convolutional neural network. Crowd features are detected using textual analysis techniques. The configurable crowd behavior for detection can be defined by crowd behavioral language.

The present invention relates to methods, systems and apparatus for capturing, integrating, organizing, navigating and querying large-scale data from high-throughput biological and chemical assay platforms. It provides a highly efficient meta-analysis infrastructure for performing research queries across a large number of studies and experiments from different biological and chemical assays, data types and organisms, as well as systems to build and add to such an infrastructure. According to various embodiments, methods, systems and interfaces for associating experimental data, features and groups of data related by structure and / or function with chemical, medical and / or biological terms in an ontology or taxonomy are provided. According to various embodiments, methods, systems and interfaces for filtering data by data source information are provided, allowing dynamic navigation through large amounts of data to find the most relevant results for a particular query.

A method of encoding knowledge is disclosed, which can be used to automatically detect problems in software application deployments. The method includes accessing a source of knowledge describing a problem known to occur in deployments of a particular software application, and which identifies a plurality of conditions associated with the problem. An encoded representation of the knowledge source is generated according to a predefined knowledge encoding methodology. The encoded representation is adapted to be applied automatically by a computer to analyze data representing a current state of a monitored deployment of the software application to detect whether the conditions and the problem exist therein. In various implementations, the encoded representation of the knowledge can include queries for deployment information, information concerning the relative importance of the conditions to a detection of the problem, and / or logical constructs for computing a confidence value in the existence of the problem and for determining whether to report the problem if some of the conditions are not true. The knowledge source can comprise a text document (such as a knowledge base article), a flowchart of a diagnostic troubleshooting method, and the like. Also disclosed are methods of at least partially automating the encoding process.

The sentimental significance of a group of historical documents related to a topic is assessed with respect to change in an extrinsic metric for the topic. A unique sentiment binding label is included to the content of actions documents that are determined to have sentimental significance and the group of documents is inserted into a historical document sentiment vector space for the topic. Action areas in the vector space are defined from the locations of action documents and singular sentiment vector may be created that describes the cumulative action area. Newly published documents are sentiment-scored by semantically comparing them to documents in the space and / or to the singular sentiment vector. The sentiment scores for the newly published documents are supplemented by human sentiment assessment of the documents and a sentiment time decay factor is applied to the supplemented sentiment score of each newly published documents. User queries are received and a set of sentiment-ranked documents is returned with the highest age-adjusted sentiment scores.

Resources of a virtualized ecosystem are intelligently secured by defining and analyzing object handling security control information for one or more logical resources in the virtualized ecosystem and deriving therefrom object properties for each of the logical resources involved in the execution of a virtual machine in any given context within the virtualized ecosystem.

Systems and methods for customizing business logic rules within a business process automation system and for processing business logic rules in a business process automation system are disclosed. The method for customizing business rules of a business logic application generally comprises serving a content page to a client browser of a client by a server that allows entering and modifying of data relating to a business logic rule, generating data by the server according to a predefined format such as a predefined XML format from information received via the content page, and automatically committing the generated data in the predefined format into a database. Preferably, a verification process such as by using DTDs (Document Type Definitions) is performed by the server prior to committing the data. The database stores data including data relating to business logic rules for implementing business logic as entries in the database and the generated data is committed into a corresponding entry in the database. Upon committing, the committed database business rule entry is ready for execution by the business logic application.

The patent describes a single location and application on a network where a user can organize public, group, and private / personal information and have this single, location accessible to the public. A new, ontology-driven portal that organizes all three categories of data according to various “facets” using underlying ontologies to define each “facet” and wherein any type of information can be classified and linked to other types of information is disclosed. An application that enables a user to effectively utilize and manage knowledge and data the user posses and allows other users to effectively and seamlessly benefit from the user's knowledge and data over a computer network is also disclosed. A method of processing content created by a user utilizing a semantic, ontology-driven portal on a computer network is described. The semantic portal application provides the user with a content base, such as a semantic form or meta-form, for creating a semantic posting. The semantic portal utilizes a knowledge data structure, such as a taxonomy or ontology, in preparing a semantic posting based on the information provided by the user via the content base. The semantic portal application prepares a preview of a semantic posting for evaluation by the user. The semantic posting is then either modified by the user or accepted and posted by the user for external parties to view.

This invention relates to the application of techniques based upon the mathematics of fractals and chaos in various fields including document verification, data encryption and weather forecasting. The invention also relates, in one of its aspects, to image processing.

The sentimental significance of a group of historical documents related to a topic is assessed with respect to change in an extrinsic metric for the topic. A unique sentiment binding label is included to the content of actions documents that are determined to have sentimental significance and the group of documents is inserted into a historical document sentiment vector space for the topic. Action areas in the vector space are defined from the locations of action documents and singular sentiment vector may be created that describes the cumulative action area. Newly published documents are sentiment-scored by semantically comparing them to documents in the space and / or to the singular sentiment vector. The sentiment scores for the newly published documents are supplemented by human sentiment assessment of the documents and a sentiment time decay factor is applied to the supplemented sentiment score of each newly published documents. User queries are received and a set of sentiment-ranked documents is returned with the highest age-adjusted sentiment scores.

Embodiments of the present invention relate to knowledge representation systems which include a knowledge base in which knowledge is represented in a structured, machine-readable format that encodes meaning.

A method and system for automatic data categorization in response to a user query. A document set is retrieved in response to the user query. A semantic parser parses the document set and produces semantic term-groups by parsing a semantic network of nodes. A seed ranker produces a plurality of advantageously spaced semantic seeds based on the semantic term-groups. A category accumulator stores the advantageously spaced semantic seeds. The semantic network of nodes is augmented with the advantageously spaced semantic seeds.

An adaptive probabilistic semantic computer-implemented system and method links semantic chains comprising subject, predicate, and object triples and an associated probability with behavioral-based chains comprising a system user, predicate, and object triples, and infers user preferences based on the linked chains. Recommendations are generated for delivery to system users based on the preference inferences. Explanations may be provided to recommendation recipients as to why they received recommendations, and the explanations may convey a sense of confidence in accordance with probabilistic semantic associations.

A system and method for precaching information on a mobile device. A precaching strategy is built for a mobile device The strategy defines a forecast of data types a user is predicted to request after the occurrence of one or more data refresh conditions. The precaching strategy is built by recognizing data usage patterns in data requested by the user or a group of users over a time period. The data usage pattern comprises data types and events that are correlated to the usage of the data. The events are used to define at least one refresh condition within the precaching strategy. The precaching strategy is executed. When the occurrence of the data refresh condition is detected, data is then retrieved from a data source, wherein the data is retrieved according to the precaching strategy. The retrieved data is transmitted to a user device cache.

A human assisted method of debugging training data used to train a machine learning classifier is provided. The method includes obtaining a classifier training data set. The training data set is then debugged using an integrated debugging tool configured to implement a debugging loop to obtain a debugged data set. The debugging tool can be configured to perform an estimation and simplification step to reduce data noise in the training data set prior to further analysis. The debugging tool also runs a panel of prediction-centric diagnostic metrics on the training data set, and provides the user prediction based listings of the results of the panel of prediction-centric diagnostic metrics.

Methods, apparatus, and computer software product for making a decision based on the semantics of formal logic are provided. In an exemplary embodiment, two custom computing apparatuses are used to resolve the satisfiability of a logical formula and provide an example. In this embodiment, the two custom computing apparatuses operate in concert to explore the space of possible satisfying examples. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules. This Abstract is submitted with the explicit understanding that it will not be used to interpret or to limit the scope or the meaning of the claims.

One or more systems and methods for knowledge pattern search from networked agents are disclosed in various embodiments of the invention. A system and a related method can utilizes a knowledge pattern discovery process, which involves analyzing historical data, contextualizing, conceptualizing, clustering, and modeling of data to pattern and discover information of interest. This process may involve constructing a pattern-identifying model using a computer system by applying a context-concept-cluster (CCC) data analysis method, and visualizing that information using a computer system interface. In one embodiment of the invention, once the pattern-identifying model is constructed, the real-time data can be gathered using multiple learning agent devices, and then analyzed by the pattern-identifying model to identify various patterns for gains analysis and derivation of an anomalousness score. This system can be useful for knowledge discovery applications in various industries, including business, competitive intelligence, and academic research.

According to an embodiment of the present invention, there is provided a method and system for emulating a knowledge representation in a UML environment. A Meta-Object Facility and UML profile are grounded in a foundation ontology. The elements representing the knowledge representation ontology are mapped to elements of UML, based on the grounded Meta-Object Facility and UML profile, thereby emulating the knowledge representation in a UML environment.

Models that encapsulate information on how remote applications are controlled and data is accessed are created to be used by a runtime agent that intelligently reasons out goal-oriented plans and execute tasks to solve problem statements generated by a user interface or other software agents. The models may be used to assemble workflows using a reasoning process. In particular, the models of the present invention include a state that includes a planning state and a navigational value. In embodiments of the invention, the models may include intelligent agents, a loop state, submodel invocation that allows the models to invoke agents over a network, and the ability to integrate the three application layers in a computer.

There is disclosed a system and method for using a knowledge representation to provide relevant information based on environmental inputs. In an embodiment, the system and method considers environmental information from members in a crowd to generate a pool of interests based on the semantic relevance concepts associated with those interests. The most prominent concepts of interest may then be the basis for presenting content to the crowd as a whole. In another embodiment, environmental inputs and other surrounding inputs are considered as a user context. The concepts may be identified as relevant from the environmental context and used to present information relevant to the user given his or her surroundings.

A system for exchanging click-through traffic between web sites of interested exchange partners on the Internet employs an intermediary web site for registering interested exchange partners and conducting a trial process for click-through traffic between exchange partners' web sites during a trial period prior to opening a bidding process of the interested exchange partners for an exchange partner's click-through traffic. Each exchange partner's web site is linked to the intermediary web site by embedding a links code which points to an addressable file stored with the intermediary web site containing the link content of each interested exchange partner's web site to be displayed in the links area on an exchange partner's web site during the trial process. The results of the exchange trials are compared with metrics for the exchange parameters that inform the exchange participants of the success of their interaction. The intermediary web site can then conduct a bidding process where the exchange participants can bid for click-through traffic from the exchange partner's web site. Based on the bidding process, the best matched exchange partners can establish an exchange relationship in which mutual click-through traffic is exchanged between the exchange partners' web sites.

Policies can combine the efficiency of rule sets with the flexible expression power of workflow engines, as well as advantages of other programming languages and engines. Consistent modelling of policy rules is provided across different levels, such as network, control, and service levels. In one system, a policy module can orchestrate rule set and workflow engines in order to evaluate different conditions of a policy. In another embodiment, a hybrid language can be used that allows rule set and other variables to be used in a business process container, workflow and other variables to be used in a rule set container, rule set and business process variables to be used in other containers. In this way, a subset of conditions in a policy can be evaluated using multiple languages and / or engines in order to enforce or evaluate a policy.

Resources of a virtualized ecosystem are intelligently secured by defining and analyzing object handling security control information for one or more logical resources in the virtualized ecosystem and deriving therefrom object properties for each of the logical resources involved in the execution of a virtual machine in any given context within the virtualized ecosystem.

An improved method of classifying examples into multiple categories using a binary support vector machine (SVM) algorithm. In one preferred embodiment, the method includes the following steps: storing a plurality of user-defined categories in a memory of a computer; analyzing a plurality of training examples for each category so as to identify one or more features associated with each category; calculating at least one feature vector for each of the examples; transforming each of the at least one feature vectors so as reflect information about all of the training examples; and building a SVM classifier for each one of the plurality of categories, wherein the process of building a SVM classifier further includes: assigning each of the examples in a first category to a first class and all other examples belonging to other categories to a second class, wherein if any one of the examples belongs to another category as well as the first category, such examples are assigned to the first class only; optimizing at least one tunable parameter of a SVM classifier for the first category, wherein the SVM classifier is trained using the first and second classes; and optimizing a function that converts the output of the binary SVM classifier into a probability of category membership.

A system and method for creating a predictive model to select an object from a group of objects that can be associated with a requested web page, wherein a configuration of the requested web page defines a subgroup of one or more selected objects from the group of objects. Exemplary embodiments of the present invention seek to provide novel solutions for determining which content object, taken from a group of content objects, will be best suited for presentation in association with a link on a web page that has been requested by a certain surfer. Each web page can include one or more links to be associated with content objects from the group.For each content object presented over a requested web page, a predictive model with relevant predictive factors is processed such that the predicted objective, the probability of success for example, is calculated. A success is defined as a surfer responding to the presented content. For example, should a surfer select a relevant content object, the probability of the objects that can be presented is calculated. Subsequently, the objects with the highest predictive expected utility are selected to be associated with the links in the web page requested by the surfer.