Abstract: A plurality of analytics in a cloud-based environment is accessed. Each of the plurality of analytics performs an operation on time series data. Within the cloud-based environment, a selected one or more of the plurality of analytics is chosen. A set of time series data is uploaded to the cloud-based environment and the selected one of the plurality of analytics is optimized on that set of time series data.

Abstract: Included herein is a method for providing seamless access to time series data located in multiple time series data storage units. A user makes a data query without knowing where the data is stored or in what format. The data request is received and parsed by a query interface and the data interface formulates one or more data requests for the specific time series data storage device where the queried data are stored. The time series data received from the data storage device is assembled by the query interface and displayed to the user.

Abstract: A service for storing time series data provides a data pipe for receiving time series data, a query pipe for making requests to the service, and a result pipe for receiving output from the service. Data sent to the query pipe is processed by an ingester that prepares metadata indices associated with blocks of incoming time series data and stores the blocks of data in a time series database and the indices in a separate index database. A query layer receives queries from the query pipe and uses the index database to determine which data blocks are needed to process the query, and then requests only those data blocks from the time series database. Processing of the query is performed within the time series database only on those data nodes that contain relevant data, and partial results are passed to an output layer for formation into a final query result which is sent out by the results pipe.

Abstract: A method for performing queries on a distributed time series data storage system is presented. The time series data storage system has a time series database that stores data blocks containing time stamped data across a plurality of computing devices. The system also includes an index database that stores an index associated with the time stamped data in each data block. The method includes the steps of sending a query, requesting indices, returning the indices, preparing a sub-query, forwarding the sub-query to an evaluator, evaluating the sub-query, performing a logical operation on each sub-query's result, receiving the sub-results at an output handler, and combining the sub-results.

Abstract: A system for storing time series data includes an ingester that prepares metadata indices associated with blocks of incoming time series data and stores the blocks of data in a time series database and the indices in a separate index database. The time series database distributes storage of the data blocks among multiple data nodes. A query layer receives queries and uses the index database to determine which data blocks are needed to process the query, and then requests only those data blocks from the time series database. Processing of the query is performed within the time series database only on those data nodes that contain relevant data, and partial results are passed to an output layer for formation into a final query result.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A multi-agent system is provided for automatically acquiring desired information from one or more information sources. The multi-agent system includes a plurality of data provider filter agents associated with the one or more information sources. The data provider filter agents are configured to search for the desired information within the respective information sources based on an assessment of the one or more information sources. The multi-agent system also includes a content extraction agent configured to acquire a plurality of articles containing the desired information from the one or more information sources based on the search.

Abstract: A robust process for automating the tuning and maintenance of decision-making systems is described. A configurable multi-stage mutation-based evolutionary algorithm optimally tunes the decision thresholds and internal parameters of fuzzy rule-based and case-based systems that decide the risk categories of insurance applications. The tunable parameters have a critical impact on the coverage and accuracy of decision-making, and a reliable method to optimally tune these parameters is critical to the quality of decision-making and maintainability of these systems.

Abstract: A robust system for automating the tuning and maintenance of decision-making systems is described. A configurable multi-stage mutation-based evolutionary algorithm optimally tunes the decision thresholds and internal parameters of fuzzy rule-based and case-based systems that decide the risk categories of insurance applications. The tunable parameters have a critical impact on the coverage and accuracy of decision-making, and a reliable method to optimally tune these parameters is critical to the quality of decision-making and maintainability of these systems.

Abstract: A method of identifying a set of entities based on a pattern of interest is provided. The method includes identifying a reference entity and identifying one or more alert categories indicative of a pattern of interest in the reference entity over a time period of interest. The method further comprises determining a matching percentage of the pattern of interest exhibited by the reference entity, in one or more entities comprising the set of entities based on the one or more alert categories. The method further comprises identifying one or more of the entities comprising the set of entities that exhibit one or more of the patterns of interest exhibited by the reference entity, based on the matching percentage.

Abstract: A method and system of forecasting reliability of an asset is provided. The method includes identifying peer units of the asset by using selected criteria, performing a search for the peer units based upon the selected criteria, and constructing local predictive models using the peer units. The method also includes estimating the future behavior of the asset based upon the local predictive models and dynamically updating the local predictive models to reflect at least one change in the criteria.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A multi-agent system is provided for automatically acquiring desired information from one or more information sources. The multi-agent system includes a plurality of data provider filter agents associated with the one or more information sources. The data provider filter agents are configured to search for the desired information within the respective information sources based on an assessment of the one or more information sources. The multi-agent system also includes a content extraction agent configured to acquire a plurality of articles containing the desired information from the one or more information sources based on the search.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A technique is provided for acquiring desired information from one or more information sources. The technique includes assessing the one or more information sources for the desired information, searching for the desired information within the one or more information sources based on the assessment, and automatically acquiring the desired information based on the search.

Abstract: A method for constructing data patterns of interest is provided. The method includes creating one or more alert clause expressions and evaluating the one or more alert clause expressions based on a parameter of interest and a plurality of conditions. The method further includes combining the one or more alert clause expressions in a selected manner to generate an alert signal. The one or more data patterns of interest are described by the one or more alert clause expressions and the alert signal.

Abstract: Searching and matching a set of query strings used for accessing information in a database directory. In this disclosure, a user community administration tool queries a database directory containing user information associated with a user community. In the user community administration tool, there is an input query generation component that generates an input query having a search pattern that includes a combination of attribute names, logical, operators and attribute values. An accessing component accesses a library of queries used for accessing the user information in the database directory. A partitioning component partitions each of the queries in the library into logical units. Each logical unit comprises a combination of an attribute name, logical operator and attribute value. A comparing component compares the search pattern of the input query to each partitioned logical unit for each of the queries in the library.

Abstract: A system, process and computer program product for underwriting a financial risk instrument application represented by at least one risk attribute is provided. Decision engines examine the at least one risk attribute associated with the financial risk instrument application and assign the application to one of a predetermined set of risk classes. A fusion engine compares the risk classes assigned by each of the decision engines and fuses the assigned risk classes into an aggregated result representative of the risk of the financial risk instrument application. The fusion engine includes a first multi-classifier fusion module that uses an associative function to fuse the assigned risk classes into a first aggregated result and a second multi-classifier fusion that uses a non-associative function to fuse the assigned risk classes into a second aggregated result.

Abstract: A method and system for fusing a collection of classifiers used for an automated insurance underwriting system and/or its quality assurance is described. Specifically, the outputs of a collection of classifiers are fused. The fusion of the data will typically result in some amount of consensus and some amount of conflict among the classifiers. The consensus will be measured and used to estimate a degree of confidence in the fused decisions. Based on the decision and degree of confidence of the fusion and the decision and degree of confidence of the production decision engine, a comparison module may then be used to identify cases for audit, cases for augmenting the training/test sets for re-tuning production decision engine, cases for review, or may simply trigger a record of its occurrence for tracking purposes. The fusion can compensate for the potential correlation among the classifiers.

Abstract: A delegated administration tool for administrating information in a database directory. The delegated administration tool enables an administrator to delegate administration and various types of administrative authority to other users within a community of users. In particular, an administrator with proper authority may create new administrative domains and assign authority referred to as delegation authority and edit authority to other users. The creation of additional administrative domains and the assignment of the delegation authority and edit authority can continue to an arbitrary level within the community.