Abstract: A system and methods are provided for identifying conversations in tweet streams. A method includes grouping tweet messages in the tweet streams into tweet groups, responsive to hashtags therefor and time intervals in which the tweet message were sent. The method further includes splitting the tweet groups into subgroups responsive to secondary hashtags and a time separation between the tweets messages. The method also includes clustering any of the subgroups into a respective same conversation responsive to word occurrences, word frequencies, and account holders. The method additionally includes merging any of the subgroups having different hashtags into the respective same conversation responsive to overlapping glossary and account lists. Each of the tweet groups and each of the subgroups correspond to a respective different one of the conversations when unable to be split, clustered, or merged.

Abstract: A system and methods are provided for identifying conversations in tweet streams. A method includes grouping tweet messages in the tweet streams into tweet groups, responsive to hashtags therefor and time intervals in which the tweet message were sent. The method further includes splitting the tweet groups into subgroups responsive to secondary hashtags and a time separation between the tweets messages. The method also includes clustering any of the subgroups into a respective same conversation responsive to word occurrences, word frequencies, and account holders. The method additionally includes merging any of the subgroups having different hashtags into the respective same conversation responsive to overlapping glossary and account lists. Each of the tweet groups and each of the subgroups correspond to a respective different one of the conversations when unable to be split, clustered, or merged.

Abstract: Various embodiments select at least one service provider from a plurality of service providers in a computing environment to satisfy at least one service request. In one embodiment, a service request is received from a user. The service request includes at least a set of service requirements to be satisfied by at least one service provider. A satisfaction level is predicted for each of a plurality of service providers with respect to each of the set of service requirements. The prediction is based on a prediction satisfaction model associated with each of the plurality of service providers. At least one service provider is selected from the plurality of service providers for satisfying the service request based on the satisfaction level predicted for each of the plurality of service providers.

Abstract: Various embodiments select at least one service provider from a plurality of service providers in a computing environment. In one embodiment, a service request is received from a user. The service request comprises at least a set of service requirements to be satisfied by at least one service provider. A satisfaction level is predicted for each of a plurality of service providers with respect to each of the set of service requirements. The prediction is based on a prediction satisfaction model associated with each of the plurality of service providers. A probability of an actual observed satisfaction level being higher than at least a user defined threshold is calculated for each of the predicted satisfaction levels. At least one service provider is selected from the plurality of service providers for satisfying the service request based on the probability that has been calculated for each satisfaction level predicted.

Abstract: Systems and methods for determining a representation of an execution trace include identifying at least one execution trace of a business process model, the business process model including parallel paths where a path influences an outcome of a decision. Path information of the business process model is determined using a processor, the path information including at least one of task execution order for each parallel path, task execution order across parallel paths, and dependency between parallel paths. A path representation for the at least one execution trace is selected based upon the path information to determine a representation of the at least one execution trace.

Abstract: Techniques are disclosed for capturing and visualizing data lineage in content management systems. For example, a method comprises the following steps. A plurality of data sets is received. Each of the data sets is associated with a party and comprises a plurality of information. A set of lineage data about one or more of the data sets is received. The lineage data comprises information about the history of a particular data set. A user interface is presented that conveys a representation of one or more of the plurality of received data sets and at least a portion of the lineage data about the history of one or more of the data sets. A command is received at the user interface to merge or unmerge two data sets in the plurality of data sets. Two or more data sets in the plurality of data sets are merged or unmerged based on the received command.

Abstract: Disclosed is a novel system and method for managing requests for an additional virtual machine. The method begins with operating at least one virtual machine accessing at least one computer resource associated with at least one physical machine within a computing cluster. One or more non-deterministic virtual machine requests for the computer resource are received. An over-utilization of the computer resource as a probability distribution function is modeled. In one example, the probability distribution function is a Beta distribution function to represent a one of a plurality of probability distribution functions. Next, an additional virtual machine on the physical machine associated with the computer resource is added in response to a probability of a utilization of the computer resource being greater than a probalistic bound on the over-utilization of the computer resource. Otherwise, the additional virtual machine is not added.

Abstract: Systems and methods for predicting trace information include determining a plurality of trace candidates for one or more traces having missing path information, the plurality of trace candidates having path information for tasks of a business process model, which includes a plurality of independent parallel paths. Probabilities that each of the plurality of trace candidates for the business process model is an actual trace are computed using a processor for the one or more traces. One of the plurality of trace candidates is identified as the actual trace based on the probabilities to predict path information of the one or more traces.

Abstract: In an exemplary embodiment of this disclosure, a computer-implemented method includes storing in a rules database one or more rules related to customer receptivity. A first subset of the rules is processed, by a computer processor, to determine a computed level of customer receptivity (LOCR) for each of one or more customers. One or more observed LOCRs are received for the one or more customers. Each observed LOCR may be based on contact with a corresponding customer of the one or more customers. One or more predicted LOCRs are predicted for the one or more customers, using one or more predictive models. Each predicted LOCR is based at least in part on an observed LOCR associated with the corresponding customer of the one or more customers. The rules in the rules database are then modified, repeatedly, to reflect the predicted LOCRs and additional predicted LOCRs after they are predicted.

Abstract: A method, information processing system, and computer program product provide on-demand information captured from wireless devices. An information request is received from an electronic device. At least one wireless communication device is identified from a set of wireless communication devices that is available to satisfy the information request. The information request is sent to the at least one wireless communication device in response to identifying the at least one wireless communication device. A set of information is received from the at least one wireless communication device that satisfies the information request. The set of information that has been received is sent to the electronic device. The information request comprises a request for a set of information of at least one information type and from a given geographical location.

Abstract: A method for training a machine learning tool to generate a prediction in a business process includes receiving a business process model corresponding to the business process, the business process model including a plurality of tasks, identifying a cycling set at a decision point in the business process model, wherein the cycling set comprises at least one task that the business process model iterates through, and building a training table by determining a total number of sub-traces and a total number of variables from a plurality of execution traces of the business process model based on the cycling set identified at the decision point, wherein a new row of the training table is created for each of the sub-traces and a new column of the training table is created for each of the variables.

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: A computer-implemented method, system, and article of manufacture for extracting and processing event data from heterogeneous computer applications. The method includes providing a computer system having software modules for performing the steps of: receiving data related to a first event; identifying a data type of the first event based on data type definitions; selecting a set of extraction rules for extracting an attribute of an event having the identified data type; extracting the first attribute from the first event data based on the set of extraction rules; and mapping the first attribute to an event attribute of a unified structure.

Abstract: A method, system and computer program product for determining health of a case. The method includes the steps of: obtaining at least one correlated trace from (i) task descriptions or (ii) data related to the task descriptions or a process instance; calculating at least one current metric using (i) the task descriptions, (ii) the data, (iii) the correlated trace or (iv) a first model; calculating at least one prognostic metric using a second model; and creating at least one combination metric from the current metric and the prognostic metric; where at least one of the steps is carried out using a computer device.

Abstract: Techniques are disclosed for identifying influence paths and expertise networks in an enterprise using provenance data associated with one or more meetings. For example, a method for processing provenance data comprises the following steps: generating provenance data for each of one or more meetings that capture one or more aspects of each meeting, correlating the provenance data between the one or more meetings, identifying a main topic and one or more sub-topics of each of the one or more meetings to establish a relation between the one or more meetings on a basis of topic, and identifying a path of influence among one or more meetings based on the correlated provenance data and the topic relation of the one or more meetings, wherein a path of influence comprises a meeting that influences one or more subsequent meetings on a basis of provenance data and topic.

Abstract: A method for generating predictions includes dividing a business process model into fragments, wherein the business process model includes task nodes and at least one decision node, determining the decision node in at least one of the fragments, determining a decision tree for each decision node, determining a probability for reaching a terminal node in each fragment, and merging the probabilities obtained from the fragments to find a probability of a future task.

Abstract: A document corpus is annotated by given annotators and aggregates of the given annotators to generate a corpus of pre-annotated documents with given annotations. The same document corpus is annotated by a subject annotator to have subject annotations. The subject annotations are decomposed into superpositions of the given annotations. The decomposed subject annotations are mapped to a most representative superposition of the given annotations. The subject annotator may be mapped to the aggregate of given annotators corresponding to the most representative compatible superposition, resulting in a meaningful new aggregate annotator.

Abstract: A computer-implemented method, system, and article of manufacture for extracting and processing event data from heterogeneous computer applications. The method includes providing a computer system having software modules for performing the steps of: receiving data related to a first event; identifying a data type of the first event based on data type definitions; selecting a set of extraction rules for extracting an attribute of an event having the identified data type; extracting the first attribute from the first event data based on the set of extraction rules; and mapping the first attribute to an event attribute of a unified structure.

Abstract: Techniques are disclosed for capturing and visualizing data lineage in content management systems. For example, a method comprises the following steps. A plurality of data sets is received. Each of the data sets is associated with a party and comprises a plurality of information. A set of lineage data about one or more of the data sets is received. The lineage data comprises information about the history of a particular data set. A user interface is presented that conveys a representation of one or more of the plurality of received data sets and at least a portion of the lineage data about the history of one or more of the data sets. A command is received at the user interface to merge or unmerge two data sets in the plurality of data sets. Two or more data sets in the plurality of data sets are merged or unmerged based on the received command.

Abstract: Under the present invention, it is determined whether sufficient resources exist for deploying a platform dependent application on its specific “native” platform in a grid environment. If not, a platform dependent portion of the application is identified, and the application is split into the platform dependent portion and a platform independent portion. Thereafter, the platform dependent portion is deployed on its corresponding native platform, while the platform independent portion is deployed on another platform in the grid environment based on available resources. Interconnections between the two portions can then be automatically generated. This can include, for example, creating remote method invocation facade interfaces, creating remote method invocation-enabled facade classes, and building a remote method invocation server for the first platform.