Abstract: A process model can be modified to be more precise by unrolling loops of the process model and evaluating or using the process model with the loops unrolled. After determining loops in a process model, sequential forward path executions of each loop identified in an input process model are counted within each trace of an event log. For each loop, a greatest common divisor (gcd) of the sequential forward path execution counts is determined. An intermediate process model is then created with the loops unrolled according to the respective gcd(s). The event log is then (re)played with the intermediate process model to identify traversed elements of the process model. Elements of the intermediate process model that were not traversed are removed to yield a more precise process model.

Abstract: A non-intrusive system which monitors a data center by detecting electromagnetic waves alleviates a resource burden on components and is inexpensive to deploy and scale within a data center. The system detects waves using omnidirectional antennas positioned throughout the data center, thus alleviating the need to physically attach directional antennas to components. The system performs a learning phase wherein representations of detected waves are mapped to occurrence of events within the data center. Once the learning phase is complete, operation of existing network monitoring tools, such as agents and probes, may cease, and the system may begin monitoring for events based on the detected waves. The system may also analyze wave data prior to the occurrence of events to identify event prediction indicators, e.g. distinctive wave values or patterns, which may be used to predict the occurrence of an event.

Abstract: A thing-sourcing project request including requirements for a thing-sourcing task that requires data input by a thing-sourcing device is received from a requestor device. A determination is made if real-time data is needed in order to complete the thing-sourcing task. In response to determining that real-time data is not needed, a determination is made if a similar thing-sourcing task has been previously completed. If not, the method determines if the thing-sourcing task can be completed using pre-existing data. If so, a data archive is searched for relevant pre-existing data that can be used to complete the thing-sourcing task. The thing-sourcing task is completed using the relevant pre-existing data, and a response to the thing-sourcing project request is transmitted to the requestor device.

Abstract: A method includes performing, by a processor: receiving a first document, the first document comprising a first plurality of sub-documents that are related to one another in a first time sequence; converting the first plurality of sub-documents to a vector format to generate a vectorized document that encodes a probability distribution of words in the document and transition probabilities between words; detecting a plurality of topics within the vectorized document, the plurality of topics being related to one another in the first time sequence; applying a process discovery algorithm to the plurality of topics to generate a model that is representative of relationships between the plurality of topics; receiving a second document containing subject matter related to a course of action, the second document comprising a second plurality of sub-documents that are related to one another in a second time sequence; using the model to generate a classification for the second document; and adjusting the course of acti

Abstract: Techniques are disclosed herein for implementing risk-adaptive system development. A model generator generates a displayed system model comprising displayed system components. A cycle generator determines a risk management cycle comprising a multiple risk management phases. The cycle generator generates a displayed risk management interface which includes multiple displayed risk management phases that are selected and sequenced within the displayed risk management interface based, at least in part, on the determined risk management cycle. The cycle generator further generates component objects that each correspond to a respective one within a set of the system components that have been selected for risk analysis. A display device displays each of the component objects within a respective one of the displayed risk management phases.

Abstract: A network device associated with a database management system receives information associated with a customer support ticket. Based on information in the database management system, a direct relationship between the received customer support ticket and a customer support ticket in the database may be determined. A graph including nodes representing customer support tickets is generated based on information in the database. Edge prediction is performed on the graph to derive relationships among the nodes in the graph. A predictive relationship between customer support tickets is derived. A relationship data set based on the direct relationship between the customer support tickets and based on the predictive relationship between the customer support tickets is generated. The relationship data set associated with the customer support ticket is communicated to the user device.

Abstract: A root cause analysis system utilizes ACs corresponding to component types in a network to construct a diagnosis model. The system generates the ACs based on component models for each component type in the network and may perform offline evaluation of the ACs using determined conditional probabilities and potential state values and cache the results. When an issue is identified at a component, the system uses a relational schema to determine a set of components on which the component depends and creates a diagnosis model for performing root cause analysis. The diagnosis model includes the component type ACs corresponding to each of the components identified in the relational schema. The system populates the diagnosis model with conditional probabilities and observed state values determined from event indications generated by the components. The system outputs a most probable explanation of the issue based on evaluation of the diagnosis model.

Abstract: A first event notification is received. The first event notification is associated with a first event. Criteria is determined based, at least in part, on the first event notification. A first component is identified based, at least in part, on the criteria a component graph. An operational status associated with the first component is determined. It is determined not to generate a second event notification based, at least in part, on the operational status.

Abstract: A method includes performing by a processor of a server: receiving a requirement description of a service for a software application, generating a migration graph that comprises vertices representing candidate service providers for the service, respectively, identifying migration capability information between the vertices of the migration graph by connecting a portion of the vertices with edges, generating a centrality metric for each of the vertices of the migration graph based on the migration capability information and a number of edges terminating at the respective vertex, grading the candidate service providers based on one of the migration capability information and the centrality metric, and deploying the service using one of the candidate service providers responsive to grading the candidate service providers receiving an architecture description for a software application that identifies a plurality of generic services, receiving a requirement description for the software application that comprises

Abstract: As a network increases in size and complexity, it becomes increasingly difficult to monitor and record relationships between components in the network. The lack of knowledge regarding component relationships can make it difficult to adequately and timely perform analysis of network issues or conditions. As a result, automated generation of a context graph that displays relationships among both hardware and software components in a network can help keep pace with a growing network and improve network analysis. The context graph may be generated based, for example, on event data (alternately referred to as event indications) generated by network components and/or event monitoring agents and network topology information. Additionally, the context graph may be augmented to display inter-component relationships based on multi-event correlations. The context graph can be used to assist in troubleshooting network issues or performing root cause analysis.

Abstract: As a network increases in size and complexity, it becomes increasingly difficult to monitor and record relationships between components in the network. The lack of knowledge regarding component relationships can make it difficult to adequately and timely perform analysis of network issues or conditions. As a result, automated generation of a context graph that displays relationships among both hardware and software components in a network can help keep pace with a growing network and improve network analysis. The context graph may be generated based, for example, on event data (alternately referred to as event indications) generated by network components and/or event monitoring agents and network topology information. Additionally, the context graph may be augmented to display inter-component relationships based on multi-event correlations. The context graph can be used to assist in troubleshooting network issues or performing root cause analysis.

Abstract: A method includes performing, by a processor: receiving a document containing subject matter related to a course of action, the document comprising a plurality of sub-documents that are related to one another in a time sequence, converting the document to a vector format to generate a vectorized document that encodes a probability distribution of words in the document and transition probabilities between words, applying a machine learning algorithm to the vectorized document to generate an estimated vectorized document, associating the estimated vectorized document with a reference document; predicting future subject matter contained in a future sub-document of the document based on the reference document, and adjusting the course of action responsive to predicting the future subject matter.

Abstract: In a computer server, a ticket element generated by an issue tracking system responsive to a client request is received, where the ticket element includes a data field including data indicative of an attribute. A database including state data stored therein is accessed responsive to receipt of the ticket element. The state data relates a plurality of states that are specific to the attribute. One of the plurality of states related by the state data is identified as corresponding to a future state of the attribute based on a current state of the attribute, and a future probability of escalation of the ticket element is computed based on the future state of the attribute responsive to identification of the one of the plurality of states as corresponding thereto. An action indicator is provided in response to the client request.

Abstract: Requirements for a thing-sourcing project that comprises a thing-sourcing task are posted to thing-sourcing participant devices. Electronic requests are received from a first group of the thing-sourcing participant devices, to participate in the task. The electronic request identifies a portion of the task that can be accomplished by the thing-sourcing participant device, but none of the electronic requests indicate that the task can be accomplished entirely by any one of the thing-sourcing participant devices. A second group of the thing-sourcing participant devices is selected from the first group of the thing-sourcing participant devices. The second group of the thing-sourcing participant devices can collectively accomplish the task, even though none of the second group of the thing-sourcing participant devices can accomplish the task individually. Execution of the thing-sourcing project by the second group of the thing-sourcing participant devices is then coordinated.

Abstract: Current behavior can be evaluated to efficiently identify behavioral anomalies with process models of different scopes and/or different degrees of precision. For meaningful behavioral evaluation of an actor (i.e., a user or a device), these multiple process models are constructed with different sets of event logs of a system. A model of a scope of an individual actor and a model of a scope of a group of actors are constructed and used for evaluation. These models of different scope expand “normal” behavior of an actor to include behavior of the group of actors. Although these process models of different scopes likely have different precision, additional models of different precision and/or different scopes can be constructed and used for behavioral evaluation. These different process models allow for behavioral variation within relevant groups of actors.

Abstract: A method includes performing operations as follows on a processor: receiving a description of a plurality of products, each product in the plurality of products having a local geographic feature that is configurable in one of a plurality of geographic configurations, receiving a description of priorities associated with the plurality of products, generating a risk based on the priorities, generating a risk mitigating treatment based on the risk, generating, for each of the plurality of products, a plurality of product localization scores corresponding to the plurality of geographic configurations, respectively, each of the plurality of product localization scores indicating a relative amount of the risk mitigated by the risk mitigating treatment with the local geographic feature having the respective geographic configuration, generating a plurality of global localization scores based on the plurality of product localization scores, each of the plurality of global localization scores corresponding to the plura

Abstract: A collaboration pattern is created by crowdsourcing participants by publishing requirements for a crowdsourcing project that includes a crowdsourcing task to the crowdsourcing participants, receiving candidate collaboration patterns for the crowdsourcing task from the crowdsourcing participants, selecting one of the candidate collaboration patterns, and executing the crowdsourcing project using the one of the candidate collaboration patterns. Related methods, systems and computer program products are provided.

Abstract: A method includes performing operations as follows on a processor: receiving an architecture description for a software application that identifies a plurality of generic services, receiving a requirement description for the software application that comprises respective values for a plurality of priority parameters for the software application, and generating a proposal that, for each of the plurality of generic services, identifies a specific cloud service for the respective generic service based on the requirement description.

Abstract: A method by a database management system provides a sequence of memory buckets that each contain a plurality of data value storage locations. For each of the memory buckets, the method responds to the plurality of data value storage locations of one of the memory buckets becoming filled from storage of data values, by generating a combined data value from combination of the data values and storing the combined data value in an unfilled one of the data value storage locations of a next one of the memory buckets in the sequence. Related computer systems and computer program products are disclosed.

Abstract: A method includes performing operations as follows on a processor: receiving an architecture description for a software application that identifies a plurality of generic services, receiving a requirement description for the software application that comprises respective values for a plurality of priority parameters for the software application, and generating a proposal that, for each of the plurality of generic services, identifies a specific cloud service for the respective generic service based on the requirement description.