Abstract: A method for discovering relationships in tabular data is provided in the illustrative embodiments. A set of documents is received, a document in the set including the tabular data. A cell in the tabular data is selected whose dependencies are to be determined. A hypothesis to use in conjunction with the cell is selected. Whether the hypothesis applies to a selected portion of the document is tested by determining whether a conclusion in the hypothesis can be computed using a function specified in the hypothesis on the selected portion. The selected portion can be a selected cell-range in the tabular data or content in a non-tabular portion of the document. The hypothesis is utilized to describe the cell relative to the selected portion.

Abstract: Mechanisms are provided for performing tabular data correction in a document. Tabular data is received and analyzed to identify at least one portion of the tabular data having an erroneous/missing data value. A functional dependency of the at least one portion of the tabular data on one or more other portions of the tabular data is determined. A correct data value for the erroneous or missing data value of the at least one portion of the tabular data is determined based on the functional dependency of the at least one portion. In addition, the tabular data is modified to replace the erroneous or missing data value with the correct data value and thereby generate a modified table data. A processing operation is then performed on the modified table data to generate a resulting output.

Abstract: A system, and computer program product for adapting tabular data for narration are provided in the illustrative embodiments. A set of categories used to organize data is identified in a first tabular portion of a document. A structure of the categories is analyzed. An inference is drawn about data in a first cell in the first tabular portion based on a position of the first cell in the structure. The first tabular portion of the document is transformed into a first narrative form using the inference.

Abstract: A method for adapting tabular data for narration is provided in the illustrative embodiments. A set of categories used to organize data is identified in a first tabular portion of a document. A structure of the categories is analyzed. An inference is drawn about data in a first cell in the first tabular portion based on a position of the first cell in the structure. The first tabular portion of the document is transformed into a first narrative form using the inference.

Abstract: A method, system, and computer program product for discovering title information for structured data in a document are provided in the illustrative embodiments. An instance of structured data is identified in a document. A search direction is identified relative to a location of the instance, wherein a title describing the instance is located in a document portion in the search direction from the instance. A sentence is selected in the document portion. A determination is made whether the selected sentence qualifies as a title by determining whether an independent clause in the selected sentence includes a verb-phrase. Responsive to the selected sentence qualifying as the title, the selected sentence is designated as a candidate title for the instance.

Abstract: A system, and computer program product for disambiguation of dependent referring expression in natural language processing are provided in the illustrative embodiments. A portion of a document in a set of document is selected, the portion including a set of dependent referring expression instances. The portion is filtered to identify an instance from a set of dependent referring expression instances by using a linguistic characteristic of the instance, the instance of dependent referring expression referring to a full expression occurring in the set of documents. The full expression is located in one member document in the set of documents by locating where the dependent referring expression is defined to be a stand-in for the full expression. The instance is resolved using the full expression such that information about the full expression is available at a location of the instance.

Abstract: A method for disambiguation of dependent referring expression in natural language processing is provided in the illustrative embodiments. A portion of a document in a set of document is selected, the portion including a set of dependent referring expression instances. The portion is filtered to identify an instance from a set of dependent referring expression instances by using a linguistic characteristic of the instance, the instance of dependent referring expression referring to a full expression occurring in the set of documents. The full expression is located in one member document in the set of documents by locating where the dependent referring expression is defined to be a stand-in for the full expression. The instance is resolved using the full expression such that information about the full expression is available at a location of the instance.

Abstract: Optimizing SQL queries for Simple Network Management Protocol (SNMP) Management Information Base (MIB) tables. An SNMP client receives a source query defined in structured query language to access data stored in one or more MIB tables. The SNMP client parses the source query into one or more queries and sub-queries and applies sets of optimization rules and heuristics to the source query to generate a query execution plan for each set of optimization rules and heuristics applied to the source query. The SNMP client selects an optimal query execution plan from the generated query execution plans and rewrites the source query as a SNMP-based query using the optimization rules and heuristics specified in the optimal query execution plan. The SNMP-based query may then be used to retrieve the data requested by the source query without performing a full query scan of the MIB tables.

Abstract: A method, system, and computer program product for improved clustering of analytic functions in a data processing environment are described. A set of instances of an analytic function receiving data input from a set of data sources is identified. A first subset of instances is configured to receive input from a first subset of data sources, and a second subset of instances is configured to receive input from a second subset of data sources. The set of instances is assigned to a cluster. The cluster begins executing in a computer in the data processing environment, when the first subset of data sources begins transmitting time series data input to the first subset of instances in the cluster.

Abstract: A method and system for optimizing SQL queries for Simple Network Management Protocol (SNMP) Management Information Base (MIB) tables. An SNMP client receives a source query defined in structured query language to access data stored in one or more MIB tables. The SNMP client parses the source query into one or more queries and sub-queries and applies sets of optimization rules and heuristics to the source query to generate a query execution plan for each set of optimization rules and heuristics applied to the source query. The SNMP client selects an optimal query execution plan from the generated query execution plans and rewrites the source query as a SNMP-based query using the optimization rules and heuristics specified in the optimal query execution plan. The SNMP-based query may then be used to retrieve the data requested by the source query without performing a full query scan of the MIB tables.

Abstract: Optimizing SQL queries for Simple Network Management Protocol (SNMP) Management Information Base (MIB) tables. An SNMP client receives a source query defined in structured query language to access data stored in one or more MIB tables. The SNMP client parses the source query into one or more queries and sub-queries and applies sets of optimization rules and heuristics to the source query to generate a query execution plan for each set of optimization rules and heuristics applied to the source query. The SNMP client selects an optimal query execution plan from the generated query execution plans and rewrites the source query as a SNMP-based query using the optimization rules and heuristics specified in the optimal query execution plan. The SNMP-based query may then be used to retrieve the data requested by the source query without performing a full query scan of the MIB tables.

Abstract: A method, system, and computer usable program product for deploying analytic functions are provided in the illustrative embodiments. A resource is identified in an analytic function specification. A set of input time series is identified for the analytic function specification. An analytic function instance corresponding to the analytic function specification is instantiated in relation to an object of the resource. Each input time series in the set of time series is located in relation to the object. The analytic function instance is associated with each input time series in the set of time series. An analysis is performed using the set of input time series and an analytic function described in the analytic function specification. The analytic function instance is instantiated if both the object and the set of data sources are present in an object graph where the analytic function instance is to be instantiated.

Abstract: A method for selective computation using analytic functions is provided in the illustrative embodiments. An object graph and information about a change therein is received. The object graph includes several objects representing several resources in an environment as well as a set of analytic function instances in relation to the objects. A set of analytic function dependencies is determined A first analytic function instance in the set of analytic function instances that has to be re-executed based on the change is identified. A re-computation graph is computed using the analytic function instance and presented. The change may be an addition, a deletion, a modification, or a combination thereof. The change may be a change in an object, in a relationship between two objects, in a relationship between an object in and an analytic function instance in the set of analytic function instances, or in an analytic function instance.

Abstract: A method, system, and computer program product for improved clustering of analytic functions in a data processing environment are described. A set of instances of an analytic function receiving data input from a set of data sources is identified. A first subset of instances is configured to receive input from a first subset of data sources, and a second subset of instances is configured to receive input from a second subset of data sources. The set of instances is assigned to a cluster. The cluster begins executing in a computer in the data processing environment, when the first subset of data sources begins transmitting time series data input to the first subset of instances in the cluster.

Abstract: A method, system, and computer usable program product for deploying analytic functions are provided in the illustrative embodiments. A resource is identified in an analytic function specification. A set of input time series is identified for the analytic function specification. An analytic function instance corresponding to the analytic function specification is instantiated in relation to an object of the resource. Each input time series in the set of time series is located in relation to the object. The analytic function instance is associated with each input time series in the set of time series. An analysis is performed using the set of input time series and an analytic function described in the analytic function specification. The analytic function instance is instantiated if both the object and the set of data sources are present in an object graph where the analytic function instance is to be instantiated.

Abstract: A method and system for optimizing SQL queries for Simple Network Management Protocol (SNMP) Management Information Base (MIB) tables. An SNMP client receives a source query defined in structured query language to access data stored in one or more MIB tables. The SNMP client parses the source query into one or more queries and sub-queries and applies sets of optimization rules and heuristics to the source query to generate a query execution plan for each set of optimization rules and heuristics applied to the source query. The SNMP client selects ah optimal query execution plan from the generated query execution plans and rewrites the source query as a SNMP-based query using the optimization rules and heuristics specified in the optimal query execution plan. The SNMP-based query may then be used to retrieve the data requested by the source query without performing a full query scan of the MIB tables.

Abstract: A method, system, and computer usable program product for deploying analytic functions are provided in the illustrative embodiments. A resource is identified in an analytic function specification. A set of input time series is identified for the analytic function specification. An analytic function instance corresponding to the analytic function specification is instantiated in relation to an object of the resource. Each input time series in the set of time series is located in relation to the object. The analytic function instance is associated with each input time series in the set of time series. An analysis is performed using the set of input time series and an analytic function described in the analytic function specification. The analytic function instance is instantiated if both the object and the set of data sources are present in an object graph where the analytic function instance is to be instantiated.

Abstract: A method, system, and computer usable program product for deploying analytic functions are provided in the illustrative embodiments. A resource is identified in an analytic function specification. A set of input time series is identified for the analytic function specification. An analytic function instance corresponding to the analytic function specification is instantiated in relation to an object of the resource. Each input time series in the set of time series is located in relation to the object. The analytic function instance is associated with each input time series in the set of time series. An analysis is performed using the set of input time series and an analytic function described in the analytic function specification. The analytic function instance is instantiated if both the object and the set of data sources are present in an object graph where the analytic function instance is to be instantiated.

Abstract: A method, system, and computer usable program product for selective computation using analytic functions are provided in the illustrative embodiments. An object graph and information about a change therein is received. The object graph includes several objects representing several resources in an environment as well as a set of analytic function instances in relation to the objects. A set of analytic function dependencies is determined. A first analytic function instance in the set of analytic function instances that has to be re-executed based on the change is identified. A re-computation graph is computed using the analytic function instance and presented. The change may be an addition, a deletion, a modification, or a combination thereof. The change may be a change in an object, in a relationship between two objects, in a relationship between an object in and an analytic function instance in the set of analytic function instances, or in an analytic function instance.

Abstract: A method, system, and computer usable program product for clustering analytic functions are provided in the illustrative embodiments. Information about a set of analytic function instances is received. Information about a set of time series is received. A subset of time series may be a set of input time series to an analytic function instance in the set of analytic function instances. An analytics clustering rule is applied to the information about the set of analytic function instances and the information about the set of time series. A subset of time series is clustered as a group in response to applying the analytics clustering rule. An analytics clustering rule may determine whether all time series in the set of input time series to an analytic function instance are members of a group, and group an output time series of the analytic function instance in the group if all time series in the set of input time series are members of the group.