Abstract:
Methods, systems, and articles of manufacture for selected VM replication and VM restart techniques are provided herein. A method includes selecting a sub-set of one or more VMs from a set of multiple VMs in a system to be replicated before an identification of one or more failed VMs in the set of multiple VMs; replicating the sub-set of one or more VMs before the identification of one or more failed VMs in the set of multiple VMs; selecting a sub-set of the identified one or more failed VMs to be restarted upon an identification of the one or more failed VMs in the set of multiple VMs in the system; and restarting the sub-set of the identified one or more failed VMs upon the identification of the one or more failed virtual machines in the set of multiple VMs.
Abstract:
Techniques for model-based analysis of a data center. A method includes creating a metamodel based on domain knowledge to represent a type of object and/or relationship of a data center, using static and dynamic configuration and data analysis techniques to discover topology of elements of the data center and represent the topology as a model that is an instance of the metamodel, using the model to perform analysis of the data center in connection with a specified task, leveraging domain knowledge represented in nodes of the metamodel to guide the analysis in terms of determining guidelines to apply to each node and determining relationships to traverse to continue the analysis, extending the domain knowledge by updating the metamodel upon discovery of additional knowledge for use in improving analysis tasks, and extending the model on-demand using dynamic analysis techniques upon detection of multiple analysis failures.
Abstract:
A computer and computer program product for managing analysis of sentiment is disclosed. A computer retrieves data used to perform the analysis of sentiment. The computer analyzes the data and the analysis of sentiment to determine if a gap exists requiring further processing to improve the analysis of sentiment. Responsive to a determination that the gap exists requiring further processing to improve the analysis of sentiment, the computer generates a task to address the gap. The computer then uses crowdsourcing to submit the generated task for processing.
Abstract:
Techniques are disclosed for integration, provisioning and management of entities and processes in a computing system such as, by way of example only, business entities and business processes. In particular, techniques are disclosed for ontology based resource provisioning and management for services. For example, such an ontology based approach can be utilized in conjunction with a business support system which may be employed in conjunction with a cloud computing environment.
Abstract:
A computer-implemented method, a computer system and a computer program product create a database of corrective actions from IT operations. The method includes obtaining a plurality of tickets from a server. A ticket in the plurality of tickets comprises text. The method also includes generating a plurality of clusters of tickets from the plurality of tickets using a machine learning clustering algorithm. In addition, the method includes identifying the corrective action in the text of the ticket using a natural language processing algorithm. The method further includes determining that the corrective action represents a successful action. lastly, the method includes storing the corrective action in the database of corrective actions, where the database associates the corrective action with the cluster of tickets.
Abstract:
An approach for a non-factoid question answering framework across tasks and domains may be provided. The approach may include training a multi-task joint learning model in a general domain. The approach may also include initializing the multi-task joint learning model in a specific target domain. The approach may include tuning the joint learning model in the target domain. The approach may include determining which task of the multiple tasks is more difficult for the multi-task joint learning model to learn. The approach may also include dynamically adjusting the weights of the multi-task joint learning model, allowing the model to concentrate on learning the more difficult learning task.
Abstract:
Systems, computer-implemented methods, and computer program products to facilitate query recommendation are provided. According to an embodiment, a system can comprise a memory that stores computer executable components and a processor that executes the computer executable components stored in the memory. The computer executable components can comprise an ontology component that can generate an ontology based on unstructured data of a description of an application programming interface. The computer executable components can further comprise a reasoner component that can identify one or more terms of the ontology that correspond semantically to a term of a query.
Abstract:
A method, system, and computer program product for automated evaluation of information retrieval systems are provided. The method accesses a natural language query from a set of natural language queries. The natural language query is associated with a query difficulty level. The method generates one or more natural language responses to the natural language natural language query. Each natural language response is associated with at least one facet of the plurality of facets. The method generates a set of feedback cues. A set of search results for the natural language query are returned. The set of search results include a highest ranked natural language response of the one or more natural language responses. The method generates an evaluation result for the HCIR system for the query difficulty level based on the one or more natural language responses, the set of search results, and the set of feedback cues.
Abstract:
Computer-implemented techniques for unsupervised event extraction are provided. In one instance, a computer implemented method can include parsing, by a system operatively coupled to a processor, unstructured text comprising event information to identify candidate event components. The computer implemented method can further include employing, by the system, one or more unsupervised machine learning techniques to generate structured event information defining events represented in the unstructured text based on the candidate event components.
Abstract:
In an approach for providing reading insight and notification on a URL with unfamiliar content for a user, a processor parses a web page to identify a URL. The URL references a subsequent web page. Prior to receiving a user interaction with the URL, a processor prefetches content of the subsequent web page. A processor determines a content domain of the prefetched content, the content domain being a summary of the prefetched content. A processor compares the content domain to a user profile, wherein the use profile is based, at least in part, on a browsing history of a user. A processor determines that the content domain is not in alignment to the user profile. A processor presents a notification to the user.