Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Techniques are disclosed for influencing behavior of enterprise operations during process enactment using provenance data. For example, a computer-implemented method of influencing a behavior of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with at least a partial actual execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed to generate an execution pattern corresponding to the at least partial actual execution of the enterprise process. The execution pattern is compared to one or more previously stored patterns.

Abstract: Methods and apparatus for optimizing resource allocation among data analysis functions in a classification system are provided. Each of the data analysis functions is characterized as a set of operating points in accordance with at least one of resource requirements and analysis quality. An operating point for each of the data analysis functions is selected in accordance with one or more constraints. The analysis functions are applied at selected operating points to optimize resource allocation among the data analysis functions in the classification system.

Abstract: An approach is provided in which atomic trust scores are computed using a atomic trust factors that are applied to a plurality of metadata. A first set of composite trust scores are computed using some of the atomic trust scores. The composite trust scores are computed using a first set of algorithms. Some of the algorithms use a factor weighting value as input to the algorithm. A second plurality of composite trust scores is computed using some of the composite trust scores that were included in the first set of scores as input. A fact and one of the second set of composite trust scores are presented to a user. The presented composite trust score provides a trustworthiness value that corresponds to the presented fact.

Abstract: A method and structure for storing information for one or more semantic objects derived from raw data. A semantic object extracted from the raw data and classified to comprise the semantic object is received, the received semantic object having one or more attributes. A summary of attributes of the semantic object by calculating one or more statistics of one or more of the one or more attributes of the received semantic object, a confidence level of the received semantic object that quantifies a degree of certainty that the received semantic object has been correctly classified and/or labeled; and a compact representation of raw data of the received semantic object are generated. Indexing information for one or more of the summary of attributes and the compact representation of the semantic object is generated.

Abstract: Systems, methods and articles of manufacture are disclosed for building and executing analytics solutions. Such a solution may provide a comprehensive analytics solution (e.g., a risk assessment, fraud detection solution, dynamic operational risk evaluations, regulatory compliance assessments, etc.). The analytics solution may perform an analytics task using operational data distributed across a variety of independently created and governed data repositories in different departments of an organization. A framework is disclosed which allows a user (e.g., a risk analyst) to compose analytical tools that can access data from a variety of sources (both internal and external to an enterprise) and perform a variety of analytic functions.

Abstract: Systems, methods and articles of manufacture are disclosed for building and executing analytics solutions. Such a solution may provide a comprehensive analytics solution (e.g., a risk assessment, fraud detection solution, dynamic operational risk evaluations, regulatory compliance assessments, etc.). The analytics solution may perform an analytics task using operational data distributed across a variety of independently created and governed data repositories in different departments of an organization. A framework is disclosed which allows a user (e.g., a risk analyst) to compose analytical tools that can access data from a variety of sources (both internal and external to an enterprise) and perform a variety of analytic functions.

Abstract: Systems, methods and articles of manufacture are disclosed for building and executing analytics solutions. Such a solution may provide a comprehensive analytics solution (e.g., a risk assessment, fraud detection solution, dynamic operational risk evaluations, regulatory compliance assessments, etc.). The analytics solution may perform an analytics task using operational data distributed across a variety of independently created and governed data repositories in different departments of an organization. A framework is disclosed which allows a user (e.g., a risk analyst) to compose analytical tools that can access data from a variety of sources (both internal and external to an enterprise) and perform a variety of analytic functions.

Abstract: Apparatus and methods for auctioning time and desktop space to product and service suppliers are provided. The apparatus and methods obtain bids from various product and service suppliers and determine which of the bids are the highest ranking bids. The particular product and service suppliers from which bids are obtained may be determined based on user preferences stored in a user profile, for example. Based on the ranking of the bids, commercial information from the product and/or service suppliers is presented to the user. Higher ranking bids are provided with larger display space on a user's client device display and are provided with a longer display time before cycling to the next lower ranking bid. In addition, multiple displays of commercial information may be provided at a same time with the size and duration of the displays being determined based on the ranking of the associated bid from the product/service supplier.

Abstract: The invention provides a system adapted to enable contextual collaboration within a computer network. The invention provides a collaboration manager that supports manipulation of collaboration spaces. The collaboration spaces contain one or more collaboration elements that have potentially different collaboration modalities. The context manager maintains resources and resource interrelationships within contexts. The resources can include collaboration elements, processes, tasks, business objects, users, and/or roles. A view generator selects a set of the resources to be displayed to a user of the computer network. The invention also includes an interface adapted to allow applications to specify commands to manipulate collaboration spaces, commands to maintain resources and resource interrelationships within contexts, and queries for context-sensitive views.

Abstract: A method and apparatus is disclosed that receives an input narrative in a particular media format, and produces therefrom a multimedia enriched version of the input narrative. In one embodiment, a method is provided for enriching an input narrative with multimedia content, wherein the method includes the step of selectively segmenting the input narrative to form queries pertaining to different portions or elements of the input narrative. The method further comprises retrieving multimedia artifacts from one or more multimedia repositories, wherein each retrieved multimedia artifact is associated with one of the queries, and selecting a subset of the retrieved multimedia artifacts, wherein the subset includes artifacts comprising different types of multimedia content. The input narrative is then combined with respective multimedia artifacts of the subset, in order to provide an enriched and enhanced narrative.

Abstract: A method and structure for storing information for one or more semantic objects derived from raw data. A semantic object extracted from the raw data and classified to comprise the semantic object is received, the received semantic object having one or more attributes. A summary of attributes of the semantic object by calculating one or more statistics of one or more of the one or more attributes of the received semantic object, a confidence level of the received semantic object that quantifies a degree of certainty that the received semantic object has been correctly classified and/or labeled; and a compact representation of raw data of the received semantic object are generated. Indexing information for one or more of the summary of attributes and the compact representation of the semantic object is generated.

Abstract: A method and system for storing a semantic object includes summarizing the attributes of a semantic object, indexing the summary of attributes, and storing the summary of attributes and the index of the summary of attributes.

Abstract: Techniques are disclosed for extracting information through analysis of provenance data. For example, a computer-implemented method of extracting information regarding an execution of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed so as to extract information about the execution of the enterprise process based on the analysis.

Abstract: Techniques are disclosed for influencing behavior of enterprise operations during process enactment using provenance data. For example, a computer-implemented method of influencing a behavior of an enterprise process comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with at least a partial actual execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. At least a portion of the generated provenance data from the graph is analyzed to generate an execution pattern corresponding to the at least partial actual execution of the enterprise process. The execution pattern is compared to one or more previously stored patterns.

Abstract: Techniques are disclosed for capturing, storing, querying and analyzing provenance data for automatic discovery of enterprise process information. For example, a computer-implemented method for managing a process associated with an enterprise comprises the following steps. Data associated with an actual end-to-end execution of an enterprise process is collected. Provenance data is generated based on at least a portion of the collected data, wherein the provenance data is indicative of a lineage of one or more data items. A provenance graph that provides a visual representation of the generated provenance data is generated, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. The generated provenance graph is stored in a repository for use in analyzing the enterprise process.

Abstract: Techniques are disclosed for validating compliance with enterprise operations based on provenance data. For example, a computer-implemented method for validating that an enterprise process is in compliance with a rule comprises the following steps. Provenance data is generated, wherein the provenance data is based on collected data associated with an actual end-to-end execution of the enterprise process and is indicative of a lineage of one or more data items. A provenance graph is generated that provides a visual representation of the generated provenance data, wherein nodes of the graph represent records associated with the collected data and edges of the graph represent relations between the records. A correlation is generated between one or more entities in the rule and one or more record types in the provenance data. One or more control points are generated in accordance with the generated correlation.

Abstract: An approach is provided for selecting one or more trust factors from trust factors included in a trust index repository. Thresholds are identified corresponding to one or more of the selected trust factors. Actions are identified to perform when the selected trust factors reach the corresponding threshold values. The identified thresholds, identified actions, and selected trust factors are stored in a data store. The selected trust factors are monitored by comparing one or more trust metadata scores with the stored identified thresholds. The stored identified actions that correspond to the selected trust factors are performed when one or more of the trust metadata scores reach the identified thresholds. At least one of the actions includes an event notification that is provided to a trust data consumer.

Abstract: An approach is provided for selecting a trust factor from trust factors that are included in a trust index repository. A trust metaphor is associated with the selected trust factor. The trust metaphor includes various context values. Range values are received and the trust metaphor, context values, and range values are associated with the selected trust factor. A request is received from a data consumer, the request corresponding to a trust factor metadata score that is associated with the selected trust factor. The trust factor metadata score is retrieved and matched with the range values. The matching results in one of the context values being selected based on the retrieved trust factor metadata score. The selected context value is then provided to the data consumer.