Abstract:
A method, system and computer program product provides a first characteristic associated with a first data set and a single data value, and a second characteristic associated with a second data set; and calculates at least one of: 1) the similarity of the first data set with the second data set based on the first and second characteristics, 2) the similarity of the first data set with the single data value based on the first characteristic and the single data value, 3) confidence indicating how well the first characteristic reflects properties of the first data set based on the first characteristic, and 4) confidence indicating how well the similarity of the first data set with the single data value reflects properties of the single data value based on the first characteristic and the single data value.
Abstract:
According to a present invention embodiment, a system utilizes a voice tag to automatically tag one or more entities within a social media environment, and comprises a computer system including at least one processor. The system analyzes the voice tag to identify one or more entities, where the voice tag includes voice signals providing information pertaining to one or more entities. One or more characteristics of each identified entity are determined based on the information within the voice tag. One or more entities appropriate for tagging within the social media environment are determined based on the characteristics and user settings within the social media environment of the identified entities, and automatically tagged. Embodiments of the present invention further include a method and computer program product for utilizing a voice tag to automatically tag one or more entities within a social media environment in substantially the same manner described above.
Abstract:
Mapping and translating reference data from multiple databases using an enterprise ontology. This is achieved by various means, including mapping values of a first database to corresponding fields within the ontology, mapping values of a second database to corresponding fields within the ontology, and determining relationships between the values of the first database and the values of the second database based on their respective mappings to common fields within the ontology.
Abstract:
A system maps data within a data source to a target data model, and comprises a computer system including at least one processor. The system determines an identifier for each data object of the data source based on the data within that data object, wherein the identifier indicates for that data object a corresponding concept within a domain ontological representation of a data model of the data source. The determined identifiers for the data objects of the data source are compared to the target data model to determine mappings between the data objects of the data source and the target data model. Data objects from the data source are extracted for the target data model in accordance with the mappings. Present invention embodiments further include a method and computer program product for mapping data within a data source to a target data model.
Abstract:
Embodiments of the invention provide an approach for creating, evolving and using a weighted semantic graph to manage and potentially identify certain information assets within an enterprise. The semantic graph may be generated by monitoring users navigating through search results which provide a set of information assets responsive to a search query. By recording the navigation path taken by many users, relationships between information assets may be identified. Further, once generated, the semantic graph may be used to present users with in indication of related information assets as part of the search results. Further still, the semantic graph may also be used to identify information assert “hubs” as well as information assets that may provide low utility to individuals within the enterprise.
Abstract:
A system maps data within a data source to a target data model, and comprises a computer system including at least one processor. The system determines an identifier for each data object of the data source based on the data within that data object, wherein the identifier indicates for that data object a corresponding concept within a domain ontological representation of a data model of the data source. The determined identifiers for the data objects of the data source are compared to the target data model to determine mappings between the data objects of the data source and the target data model. Data objects from the data source are extracted for the target data model in accordance with the mappings. Present invention embodiments further include a method and computer program product for mapping data within a data source to a target data model.
Abstract:
A method, information processing system, and computer program storage product manage connections between a virtual world and a social network. A set of virtual world information and a set of social network information are analyzed. A graph including a plurality of vertices is generated. Each vertex represents one of virtual world information and social network information. Each vertex is coupled to at least one other vertex by a respective edge. At least one edge of the graph couples a first vertex representing virtual world information and a second vertex representing social network information. At least one vertex is determined to be an articulation point having a respective edge. The removal of the respective edge of the articulation point causes a disconnection of the virtual world information from the social network information within the graph. A user is notified via a graphical user interface that the graph comprises the articulation point.
Abstract:
Embodiments of the invention provide an approach for creating, evolving and using a weighted semantic graph to manage and potentially identify certain information assets within an enterprise. The semantic graph may be generated by monitoring users navigating through search results which provide a set of information assets responsive to a search query. By recording the navigation path taken by many users, relationships between information assets may be identified. Further, once generated, the semantic graph may be used to present users with in indication of related information assets as part of the search results. Further still, the semantic graph may also be used to identify information assert “hubs” as well as information assets that may provide low utility to individuals within the enterprise.
Abstract:
A method, system and computer program product for identifying reference data tables in an Extract-Transform-Load (ETL) process, by identifying, by operation of one or more computer processors, at least a first reference data operator in the process, wherein the first reference data operator references one or more tables and evaluating at least a first table referenced by the reference data operator to determine whether the first table is a reference data table by assigning a score to the first table, wherein the score is indicative of the likelihood that the first table is a reference data table and wherein a reference data table contains a set of values that describes other data.
Abstract:
Techniques are disclosed for identifying transcoding tables in an Extract-Transform-Load (ETL) process, by identifying, by operation of one or more computer processors, records passing through an operator configured to replace values in the records with values from at least one table linked to the operator before being sent to an output table, wherein the operator specifies an operation for extracting, transforming, or loading data stored in one or more source systems into storage by a target system, and evaluating at least a first table linked to the operator to determine whether the first table is a transcoding table by assigning a score to the first table, wherein the score is indicative of the likelihood that the first table is a transcoding table, wherein a transcoding table is used to harmonize values from a plurality of tables in the one or more source systems to a table in the target.