Abstract: The present invention is directed to a system for managing business knowledge expressed as statements, preferably sentences using a vocabulary, where such statements may be automated by the generation of programming language source code or computer program instructions. As such, the present invention also manages software design specifications that define, describe, or constrain the programming code it generates or programs with which it or the code it generates is to integrate. All information managed within the present invention is maintained within a relational database that is encapsulated within an object-oriented model. Each object in this model is subject to version control and administration using permissions. Each user of the system is an object and belongs to one or more groups. Users and groups may be granted privileges. Objects may be created, examined, used, modified, deleted, or otherwise operated upon only if corresponding permission or privilege has been granted.

Abstract: A computer implemented method and system is disclosed herein for constructing reports, comprising the steps of providing the information of interest of a user and generating the writing style of a user. The step of generating the writing style further comprises the steps of generating a prose style and report pattern style, generating the rendering style of a user, and applying the writing style to the information of interest to provide the constructed report. The method of deriving the prose style comprises the steps of deriving preferred equivalent name set entry sets, preferred equivalent pattern specification sets; and embellishment patterns.

Abstract: Systems and techniques for facilitating link analysis may be implemented by storing data regarding a knowledge domain. The data may include information about nodes and reflective links. Each node may represent an entity in the knowledge domain. Each reflective link may represent a relationship between a respective pair of nodes, including a first node and a second node. Each reflective link may include information about a first set of characteristics for the relationship of the first node to the second node and a second set of characteristics for the relationship of the second node to the first node. By allowing the first set of characteristics to be different from and to include reflective characteristics of the second set of characteristics, different properties and functions can be associated with each direction of the reflective link. Link analysis may be performed on nodes and reflective links to more effectively infer new knowledge.

Abstract: A method and system for classifying messages of a discussion thread as questions is provided. A classification system generates a classifier to classify messages of discussion threads as question messages or non-question messages. The system trains the classifier using the feature vectors and input classifications derived from a training set of discussion threads. After the classifier is trained, the classification system uses the classifier to classify messages within a corpus of discussion threads as question or non-question messages. To classify a message, the classification system generates a feature vector for the messages and submits that feature vector to the classifier. The classifier generates a score for the message indicating a likelihood that the message is a question message.

Abstract: A system and method of automatically generating workflows. Generating the workflows is accomplished by obtaining customer requirements, providing a knowledge base including at least one service description and selecting at least one combination of service descriptions from the at least one service description based on satisfaction of the customer requirements and satisfaction of determination of connectivity between service descriptions for each combination of the at least one combination. At least one valid workflow model is generated by inference, each workflow model including a combination of the at least one combination.

Abstract: Embodiments of the invention provide an RBE that uses a logical abstraction for a set of application rules that allows the rules to be implemented, presented and modified efficiently. For one embodiment, rules logic for implementing a set of application rules is stored. The rules logic is specified by a processing sequence using one or more application factors, each of which has one or more application factor values. A plurality of entries corresponding to each application factor is separately stored. Each entry contains a data point set having one or more data points and a result corresponding to the data point set. Each of the one or more data points of a data point set corresponds to a distinct factor value.

Abstract: Embodiments of the present invention include the steps of (i) defining a first resource containing information objects defining a set of users; (ii) discovering said information objects based on said first resource definition; (iii) associating each of said information objects with a user from said set of users and said first resource. Embodiments of the present invention can include delegation of discovery tasks to allow additional resources to be defined.

Abstract: A system and method that are directed towards developing a computer user interface employing a Personal Support Infrastructure (PSI) stack. The PSI stack is arranged to represent various layers of a human being employing a holistic approach. In one embodiment, the PSI stack may enable organization, development, and solicitation of requirements for the development of a human-machine interface, such as for a mobile device, and the like. In one embodiment, the PSI stack is configured as a data structure that may be populated with elicitations oriented towards developing the set of human-machine interface requirements.

Abstract: Systems and methods that cleanse data in Extract, Transform, Load environments (ETL), via employing an outlier detect component that is positioned in data pipeline to data warehouse(s). Such outlier detect component employs a cluster mining model to split data into normal and outlier data. Different predictive models can be employed to detect outliers in different data slices to enhance the accuracy of the predictions. In addition, a graphical user interface (GUI) enables a user to interact with cluster groups that are created and/or analyzed by the outlier detect component.

Abstract: A system for learning an attention model for an image based on user navigation actions while viewing the image is provided. An attention model learning system generates an initial attention model based on static features derived from the image. The learning system logs the actions of users as they view the image. The learning system identifies from the actions of the users those areas of the image that may be of user interest: After the learning system identifies areas that may be of user interest, the learning system attempts to identify attention objects based on those identified areas. After identifying the user attention objects, the learning system updates the attention model for the image to reflect the additional information provided by the user attention objects.

Abstract: A system for identifying keywords in search results includes a plurality of neurons connected as a neural network, the neurons being associated with words and documents. An activity regulator regulates a minimum and/or maximum number of neurons of the neural network that are excited at any given time. Means for displaying the neurons to a user and identifying the neurons that correspond to keywords can be provided. Means for changing positions of the neurons relative to each other based on input from the user can be provided. The change in position of one neuron changes the keywords. The input from the user can be dragging a neuron on a display device, or changing a relevance of two neurons relative to each other. The neural network can be excited by a query that comprises words selected by a user. The neural network can be a bidirectional network. The user can inhibit neurons of the neural network by indicating irrelevance of a document.

Abstract: One implementation provides a method for modifying a knowledge base on a client device. The method includes receiving input from a user of the client device specifying a first proposed modification to the knowledge base, modifying the knowledge base as specified by the first proposed modification, and subsequently receiving electronic information from a host server specifying a second proposed modification to the knowledge base. The method further includes comparing the second proposed modification to the first proposed modification previously made to the knowledge base and, upon comparison, determining whether to modify the knowledge base as specified by the second proposed modification.

Abstract: According to one embodiment, the Web pages that match a user's designated collection condition are collected from a plurality of Web sites. The collected Web pages are divided into a plurality of clusters, based on URL information of the Web pages. A date expression is extracted from Web pages included in each of the clusters. A typical date expression form is determined for each of the clusters, based on the extracted date expression. The Web pages included in each of the clusters are divided into a plurality of items, based on the date expression form. The items are sorted for each of the clusters in order of time, based on date expressions corresponding to the items. Time-series data is generated for each of the clusters by sorting the items.

Abstract: A computer-implemented network structure includes a semantic network machine comprised of nodes containing informational contents and links containing relational contents. Relational contents describe the relationship between linked nodes. Some of the nodes are semantic Janus units. Based on time-variable states of each semantic Janus unit, the semantic Janus units perform operations on nodes and links. The operations are focused on selected portions of the semantic network machine such that each semantic Janus unit need not deal with all possible informational and relational contents within the semantic network machine. The computational resources of the computer network are thereby efficiently managed, and artificial intelligence tasks such as inferential retrieval are performed quicker. The amount of data that is processed is substantially reduced by focusing on bundled information.

Abstract: Disclosed are methods and apparatus for updating at least one prediction model for use by at least one interactive server. Each interactive server performs a plurality of actions in the context of a plurality of input attributes values of an input dataset wherein the actions are selected based on each prediction model. contextual data are automatically and continually obtained from the interactive server as it performs the plurality of actions. A learning model is automatically and continually updated based on all of the obtained contextual data. An updated prediction model and a prediction of a probability of an outcome using the updated prediction model are generated. A prediction is generated and an action of the plurality of actions based on the prediction is selected. The selection action is performed.

Abstract: Systems, computer program products, and associated methods provide for selecting between manual and automatic operating modes based upon previous experience as quantified by confidence indicators. Confidence indicators are values that may each represent a likelihood that an associated candidate class or candidate object matches an incoming message, for example. Confidence indicator values may be updated according to previous manual selections or rejections of the associated class or object, for example. In an exemplary response management system, the selections may be for modes of operation that relate to classification of an incoming message, and/or suggestion of objects, for example.

Abstract: An electronic circuit for use in providing computational decision-making capabilities. The circuit implements a hierarchy of decision-making cells, with outputs derived from input signals supplying argument values, configuration signals for controlling the decision making model and wires between cells defining relationships between cells that modify the decision-making model of dependent cells. The cells are primarily characterized by modified values that may represent outputs although they may have a variety of other function features such as importance values and threshold values. The arguments are characterized by argument values that may represent inputs. The arguments are associated with particular cells and the values of the arguments associated with a given cell are combined to determine the value of that cell. The wires between different cells define different types of functional relationships between them.

Abstract: Systems and methods are provided for constructing a classification architecture for a pattern recognition classifier that determines an associated occupant class of an occupant within a vehicle. A plurality of occupant classes are defined, with at least one of the occupant classes having an associated set of subclasses (202). A hierarchy of subclass partitions is determined based on a degree of similarity between subclasses associated with a given occupant class (210). Each successive partition in the hierarchy is an immediate partition of the preceding partition. The following is then performed iteratively until a termination event occurs. A subclass partition is selected according to the determined hierarchy (216/230). The fitness of a classifier model having an architecture derived from the selected subclass partition is evaluated (220).

Abstract: A method of developing a rule-constrained statistical pattern recognizer applicable to price formation recognition includes assembling input data containing examples of patterns to be recognized and establishing mandatory recognition rules. The recognition rules are programmed to construct an underspecified or underconstrained recognition model which is applied to the assembled data to produce candidate patterns. The candidate patterns are reviewed and identified as valid or invalid and for each pattern type a residual statistical model is produced based on the candidate patterns identified as valid. A filter is used to ensure that custom conditions such as duration relationships, height relationships and volume requirements are met.

Abstract: A neural network component includes a plurality of inputs, at least one processing element, at least one output, and a digital memory storing values at addresses respectively corresponding to the at least one processing element, wherein the at least one processing element is arranged to receive a value from the digital memory in response to an input signal, and is instructed to execute one of a plurality of operations by the value that is received from the digital memory.