Abstract: A call center system for allocating problem tickets for technical services by using a pull model auction to select an agent to work on the problem ticket. When the call center receives an order for a technical service, it develops a complexity estimate for the tasks specified in the problem ticket, and calculates deadlines for completing the problem ticket and for conducting the auction. Invitations to bid on the problem ticket are sent to potential agents on a bidder's list. The winning bid is selected from among the bids received back from the potential agents, and, after evaluating the bids, the problem ticket is transferred to the winning agent.

Abstract: Methods and arrangements for identifying root causes of system failures in a distributed system said method including: utilizing at least one processor to execute computer code that performs the steps of: recording, in a storage device, collected machine state data, wherein the collected machine state data are added to historical machine state data; creating, based on the historical machine state data, a healthy map model; detecting at least one failed machine state in the distributed system; comparing the failed machine state against the healthy map model; identifying, based on the comparison, at least one root cause of the failed machine state; and displaying, on a display device, a ranked list comprising the at least one root cause. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods and arrangements for identifying related data in different data sets to assist in searching the data sets. A first data asset and a second data asset are accessed. Common entities are identified between the first and second data assets. A score is determined for the relationship between the first and second data assets, based on the identified common entities. One or more relationship contexts are determined for the relationship between the first and second data assets, and the relationship score and one or more relationship contexts are used to join at least a portion of each of the first and second data assets as a basis for subsequent searching. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods and arrangements for identifying root causes of system failures in a distributed system said method including: utilizing at least one processor to execute computer code that performs the steps of: recording, in a storage device, collected machine state data, wherein the collected machine state data are added to historical machine state data; creating, based on the historical machine state data, a healthy map model; detecting at least one failed machine state in the distributed system; comparing the failed machine state against the healthy map model; identifying, based on the comparison, at least one root cause of the failed machine state; and displaying, on a display device, a ranked list comprising the at least one root cause. Other variants and embodiments are broadly contemplated herein.

Abstract: Methods and arrangements for identifying related data in different data sets to assist in searching the data sets. A first data asset and a second data asset are accessed. Common entities are identified between the first and second data assets. A score is determined for the relationship between the first and second data assets, based on the identified common entities. One or more relationship contexts are determined for the relationship between the first and second data assets, and the relationship score and one or more relationship contexts are used to join at least a portion of each of the first and second data assets as a basis for subsequent searching. Other variants and embodiments are broadly contemplated herein.

Abstract: A computer-implemented method, computer program product, and computing system for implementing multi-temporal tables in a database is described. One or more databases are utilized, wherein the one or more databases implement a first temporal table that includes a first and a second time domain. The one or more databases are enabled to implement a second temporal table that includes at least a third time domain, wherein the second temporal table is associated with the first temporal table.

Abstract: Methods and arrangements for managing and enhancing workflow. A work item is accepted and the is routed from a first node to a second node based on a predictive analytics model. The predictive analytics model is validated, and is reconfigured responsive to the validating.

Abstract: Methods and arrangements for managing and enhancing workflow. A work item is accepted and the is routed from a first node to a second node based on a predictive analytics model. The predictive analytics model is validated, and is reconfigured responsive to the validating.

Abstract: A computer-implemented method, computer program product, and computing system for implementing multi-temporal tables in a database is described. One or more databases are utilized, wherein the one or more databases implement a first temporal table that includes a first and a second time domain. The one or more databases are enabled to implement a second temporal table that includes at least a third time domain, wherein the second temporal table is associated with the first temporal table.

Abstract: Systems and methods for dynamic product bundling are described herein. For example, embodiments dynamically generate product bundle for customer within a particular segment in view of that customer's interest in a particular product. Embodiments determine customer affinity, customer commonality, and product complementarity and use this information to dynamically generate and optimize product bundles for customers interested in one or more products.

Abstract: Methods and arrangements for managing and enhancing workflow. A work item is accepted and the is routed from a first node to a second node based on a predictive analytics model. The predictive analytics model is validated, and is reconfigured responsive to the validating.

Abstract: Systems and methods for dynamic product bundling are described herein. For example, embodiments dynamically generate product bundle for customer within a particular segment in view of that customer's interest in a particular product. Embodiments determine customer affinity, customer commonality, and product complementarity and use this information to dynamically generate and optimize product bundles for customers interested in one or more products.

Abstract: Techniques for extracting information from a formatted document are provided. The techniques include combining one or more visual layout rules, one or more mark-up rules and one or more text-based rules in connection with a formatted document, and specifying one or more rules from the one or more visual layout rules, one or more mark-up rules and one or more text based rules to extract information from the formatted document.

Abstract: Methods and arrangements for managing and enhancing workflow. A work item is accepted and the is routed from a first node to a second node based on a predictive analytics model. The predictive analytics model is validated, and is reconfigured responsive to the validating.

Abstract: A business rule processing system automatically processes dynamic business rules in a content management system, allowing frequent updates to the business rules. The updates can be automatically adapted by the system without restarting the content management system. The system utilizes a stand-alone rule engine. Business logic is encoded as business rule definition files using a platform-independent language; the business rule definition files are stored in a central business rule repository. The business rules are managed and executed by the rules engine; the rules engine provides business rule processing services to other parts of the content management system. The system reduces development and maintenance cost, accelerates the business rule update cycle, and simplifies administration efforts.

Abstract: A method, apparatus, architecture and computer program product for populating a service request is disclosed. A service request is modeled to determine the steps involved. The data is missing from a service request for each step of the request is assessed. The data sources for the modeled request are identified. The relevant data is extracted from the identified data sources. The service request is populated with the extracted data. A service request is executed by executing at least one process step acting on the populated service request.

Abstract: Techniques for extracting information from a formatted document are provided. The techniques include combining one or more visual layout rules, one or more mark-up rules and one or more text-based rules in connection with a formatted document, and specifying one or more rules from the one or more visual layout rules, one or more mark-up rules and one or more text based rules to extract information from the formatted document.

Abstract: The analysis of OLAP data to determine user-relevant information firstly generates a set of queries based on said preferences. Each query is evaluated sequentially against the OLAP data to give a query result. For each evaluated query in turn, it is determined whether said result is relevant to the user on the basis of conditions derived from the user preferences. An output results set is formed consisting of the relevant results. Further, if a previous query result containing a common measure was determined not to be relevant, then a subsequent query can be omitted from evaluation.

Abstract: A method of detecting tasks performed by users wherein a single task is a sequence of web URLs invocation. Task patterns are detected in web logs to identify tasks performed by users and analyze task trends over time, across corporate divisions and geographies. A grammar-based framework is used to model and detect tasks from web log patterns. The framework has two components: a declarative unit—to generate a task grammar, and a processing unit—to detect tasks from access logs by generating a state machine for applying the task grammar to the tokens associated with the access records. By analyzing user tasks, rather than just URLs, useful business information can be extracted.

Abstract: A call center system for allocating problem tickets for technical services by using a pull model auction to select an agent to work on the problem ticket. When the call center receives an order for a technical service, it develops a complexity estimate for the tasks specified in the problem ticket, and calculates deadlines for completing the problem ticket and for conducting the auction. Invitations to bid on the problem ticket are sent to potential agents on a bidder's list. The winning bid is selected from among the bids received back from the potential agents, and, after evaluating the bids, the problem ticket is transferred to the winning agent.