Abstract: A system and method for facilitating modifying a runtime application behavior and/or functionality of a networked software application, whereby UI-driven data model modifications effectively propagate back to the UI of the runtime application. The example method includes employing the runtime user interface display screen to present one or more indicators for one or more customizable user interface features of the runtime user interface display screen; generating one or more signals based upon user input, wherein the user input indicates a modification to be made to the one or more customizable user interface features; initiating one or more changes to a computing object and data model associated with the computing object in accordance with the one or more signals; and displaying a modified user interface display screen in accordance with the one or more changes.

Abstract: A system that manages a unified sandbox environment activates a plurality of components in the unified sandbox environment, each component being configured to manage the lifecycle of its own component data. The system orchestrates an operation across the unified sandbox environment, the orchestrating including delegating one or more operations to the components, the components being configured to wait until all delegated operations are completed successfully before committing changes based on the delegated operations. The system manages a central label repository including distributing labels to the components, the components being configured to associate the centrally managed labels with versions of their respective component data. The system then creates a unified sandbox view across the respective component data of all components based on a selection of one or more of the centrally managed labels.

Abstract: A mechanism and accompanying method adapted for use with a user interface for manipulating complex data strings. In an example embodiment, the method includes providing a dialog box that includes a first user option to input data pertaining to a complex data string; using data input pertaining to the complex data string to selectively verify that portions of the complex data string represent valid portions; providing a first user option via the dialog box to employ data input pertaining to the complex data string as one or more search criteria to selectively perform a search of preexisting complex data strings; and providing search results in response thereto, wherein the search results are displayed within the dialog box. In a specific embodiment, the method further includes providing a mechanism via the dialog box to trigger creation of a complex data string that a user has specified via the dialog box when search results for the complex data string to be created do not include a match.

Abstract: A system that manages a unified sandbox environment activates a plurality of components in the unified sandbox environment, each component being configured to manage the lifecycle of its own component data. The system orchestrates an operation across the unified sandbox environment, the orchestrating including delegating one or more operations to the components, the components being configured to wait until all delegated operations are completed successfully before committing changes based on the delegated operations. The system manages a central label repository including distributing labels to the components, the components being configured to associate the centrally managed labels with versions of their respective component data. The system then creates a unified sandbox view across the respective component data of all components based on a selection of one or more of the centrally managed labels.

Abstract: A system and method for facilitating modifying a runtime application behavior and/or functionality of a networked software application, whereby UI-driven data model modifications effectively propagate back to the UI of the runtime application. The example method includes employing the runtime user interface display screen to present one or more indicators for one or more customizable user interface features of the runtime user interface display screen; generating one or more signals based upon user input, wherein the user input indicates a modification to be made to the one or more customizable user interface features; initiating one or more changes to a computing object and data model associated with the computing object in accordance with the one or more signals; and displaying a modified user interface display screen in accordance with the one or more changes.

Abstract: Systems and methods for parallel stream item counting are disclosed. A data stream is partitioned into portions and the portions are assigned to a plurality of processing cores. A sequential kernel is executed at each processing core to compute a local count for items in an assigned portion of the data stream for that processing core. The counts are aggregated for all the processing cores to determine a final count for the items in the data stream. A frequency-aware counting method (FCM) for data streams includes dynamically capturing relative frequency phases of items from a data stream and placing the items in a sketch structure using a plurality of hash functions where a number of hash functions is based on the frequency phase of the item. A zero-frequency table is provided to reduce errors due to absent items.

Abstract: A mechanism and accompanying method adapted for use with a user interface for manipulating complex data strings. In an example embodiment, the method includes providing a dialog box that includes a first user option to input data pertaining to a complex data string; using data input pertaining to the complex data string to selectively verify that portions of the complex data string represent valid portions; providing a first user option via the dialog box to employ data input pertaining to the complex data string as one or more search criteria to selectively perform a search of preexisting complex data strings; and providing search results in response thereto, wherein the search results are displayed within the dialog box. In a specific embodiment, the method further includes providing a mechanism via the dialog box to trigger creation of a complex data string that a user has specified via the dialog box when search results for the complex data string to be created do not include a match.

Abstract: Systems and methods are provided for real-time classification of streaming data. In particular, systems and methods for real-time classification of continuous data streams implement micro-clustering methods for offline and online processing of training data to build and dynamically update training models that are used for classification, as well as incrementally clustering the data over contiguous segments of a continuous data stream (in real-time) into a plurality of micro-clusters from which target profiles are constructed which define/model the behavior of the data in individual segments of the data stream.

Abstract: A method of querying a hierarchically organized sensor network, said network being sensor network with a global coordinator node at a top level which receives data from lower level intermediate nodes which are either leader nodes for lower level nodes or sensor nodes, wherein a sensor node i at a lowest level receives a signal Y(i,t) at time t, said method including constructing a sketch Swkt=(Swkt1, . . . , Swktn) for an internal node k from S wkt j = ? i ? LeafDescendents ? ( k ) ? ? q = 1 i ? b wiq · r iq j , wherein component Swktj is a sketch of a descendent of node k, ritj is a random variable associated with each sensor node i and time instant t wherein index j refers to independently drawn instantiations of the random variable, bit bwit represents a state of sensor node i for signal value w=Y(i,t) at time t, and LeafDescendents(k) are the lowest level sensor nodes under node k, wherein said sketch is adapted for responding to queries regarding a state of said network.

Abstract: A method of querying a hierarchically organized sensor network, said network being sensor network with a global coordinator node at a top level which receives data from lower level intermediate nodes which are either leader nodes for lower level nodes or sensor nodes, wherein a sensor node i at a lowest level receives a signal Y(i,t) at time t, said method including constructing a sketch Swkt=(Swkt1, . . . ,Swktn) for an internal node k from S wkt j = ? i ? LeafDescendents ? ( k ) ? ? q = 1 i ? b wiq · r iq j , wherein component Swktj is a sketch of a descendent of node k, ritj is a random variable associated with each sensor node i and time instant t wherein index j refers to independently drawn instantiations of the random variable, bit bwit represents a state of sensor node i for signal value w=Y(i,t) at time t, and LeafDescendents(k) are the lowest level sensor nodes under node k, wherein said sketch is adapted for responding to queries regarding a state of said network.

Abstract: Systems and methods for parallel stream item counting are disclosed. A data stream is partitioned into portions and the portions are assigned to a plurality of processing cores. A sequential kernel is executed at each processing core to compute a local count for items in an assigned portion of the data stream for that processing core. The counts are aggregated for all the processing cores to determine a final count for the items in the data stream. A frequency-aware counting method (FCM) for data streams includes dynamically capturing relative frequency phases of items from a data stream and placing the items in a sketch structure using a plurality of hash functions where a number of hash functions is based on the frequency phase of the item. A zero-frequency table is provided to reduce errors due to absent items.

Abstract: A system and method for providing similarity indexing and searching in multi-dimensional databases. In one aspect, given a set of data points in a multidimensional space, the values of the data points on each dimension are partitioned into a plurality of grids, wherein each grid is assigned a grid value. Given a target data point, similarity candidates (i.e., data points that are similar to the target data point) are identified based on matching grid values. An inverted grid index comprising an index on the data points falling into each grid of each dimension is utilized to identify similarity candidates. A similarity selection process is employed to select the closest identified similarity candidates for output, which utilizes a similarity function to measure the closeness of each identified similarity candidate to the target data point. A preferred similarity function is one that considers a subset of the dimensions in which a point falls within a similar grid of the target point.

Abstract: A method for dynamically placing objects in slots on a web page in response to a current client request for the web page comprises the steps of classifying users into user groups based one or more user-characteristics, accumulating self-learning data based on user click behavior for each user group, matching the current client request with a corresponding user group and scheduling real-time selection of the slots for the objects on the web page based on the self-learning data of the corresponding user group.

Abstract: A rating of a plurality of ratings is predicted. The rating is associated with a user of a plurality of users and the rating corresponds to an item of a plurality of items. One of the plurality of ratings, corresponding to at least one of the plurality of items, is provided for each of the plurality of users. A predictability relation between ones of the plurality of users and other ones of the plurality of users is calculated based on ratings provided by users. One of a plurality of nodes is assigned to each of the plurality of users. Ones of the plurality of nodes are connected with other ones of the plurality of nodes by a plurality of edges based on the predictability relation. A graph which includes the plurality of nodes and the plurality of edges is searched for a path from a node assigned to the user of the plurality of users to another node assigned to another user of the plurality of users.

Abstract: A graph taxonomy of information which is represented by a plurality of vectors is generated. The graph taxonomy includes a plurality of nodes and a plurality of edges. The plurality of nodes is generated, and each node of the plurality of nodes is associated with ones of the plurality of vectors. A tree hierarchy is established based on the plurality of nodes. A plurality of distances between ones of the plurality of nodes is calculated. Ones of the plurality of nodes are connected with other ones of the plurality of nodes by ones of the plurality of edges based on the plurality of distances. The information represented by the plurality of vectors may be, for example, a plurality of documents such as Web Pages.

Abstract: A method of analyzing information in the form of a plurality of data values. The plurality of data values represent a plurality of objects. The plurality of data values are distributed in a data space. A set of features which characterize each of the plurality of objects is identified. The plurality of data values are stored in a database. Each of the plurality of data values corresponds to at least one of the plurality of objects based on the set of features. Ones of the plurality of data values stored in the database are partitioned into a plurality of clusters. A respective orientation associated with a position in data space of data values which are contained in each respective cluster of the plurality of clusters is calculated based on the set of features. If desired, information may be analyzed for finding peer groups in e-commerce applications.

Abstract: A system and method are provided to analyze information stored in a computer data base by detecting clusters of related or correlated data values. Data values stored in the data base represent a set of objects. A data value is stored in the data base as an instance of a set of features that characterize the objects. The features are the dimensions of the feature space of the data base. Each cluster includes not only a subset of related data values stored in the data base but also a subset of features. The data values in a cluster are data values that are a short distance apart, in the sense of a metric, when projected onto a subspace that corresponds to the subset of features of the cluster. A set of k clusters may be detected such that the average number of features of the subsets of features of the clusters is l.

Abstract: Information is analyzed in the form of a plurality of data values that represent a plurality of objects. A set of features that characterize each object of the plurality of objects is identified. The plurality of data values are stored in a database. Each data value corresponds to at least one of the plurality of objects based on the set of features. Ones of the plurality of data values stored in the database are partitioned into a plurality of clusters. Each cluster of the plurality of clusters is assigned to one respective node of a plurality of nodes arranged in a tree hierarchy. Ones of the plurality of nodes of the tree hierarchy are traversed. If desired, information may be analyzed for finding peer groups in e-commerce applications.

Abstract: A computerized method of online mining of inference rules in a large database. The method is comprised of two stages, a preprocessing stage followed by an online rule generation stage. The pro-processing stage is further defined to be a two step process that involves the generation of large itemsets. The present method defines large itemsets by how the items in the itemsets relate to each other rather than their level of presence. The measure by which itemsets are said to relate to each other is defined by a computed figure of merit, K1. The first substep of the preprocessing stage involves finding those itemsets that possess a minimum computer collective strength of K1. From those found itemsets, a second user supplied input, K2 is used to prune those itemsets with inference strength below K2.

Abstract: A method of analyzing information in the form of a plurality of data records. Each data record includes one or more data values. The data values are partitioned into a plurality of data signatures. Data values of data signatures are compared to data values of data records. Based on the result of the comparison an index is associated with each data record. A bound corresponding to the index is calculated based on a user defined target value and an objective function. If desired, information may be analyzed for finding peer groups in e-commerce applications.