Patent application number | Description | Published |
20090048876 | SYSTEM AND PROCESS FOR A FUSION CLASSIFICATION FOR INSURANCE UNDERWRITING SUITABLE FOR USE BY AN AUTOMATED SYSTEM - 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. The reliability of each classifier can be represented by a static or dynamic discounting factor, which will reflect the expected accuracy of the classifier. A static discounting factor is used to represent a prior expectation about the classifier's reliability, e.g., it might be based on the average past accuracy of the model, while a dynamic discounting is used to represent a conditional assessment of the classifier's reliability, e.g., whenever a classifier bases its output on an insufficient number of points it is not reliable. | 02-19-2009 |
20090150212 | Method for identifying entities exhibiting patterns of interest related to financial health - 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. | 06-11-2009 |
20140172866 | SYSTEM FOR STORAGE, QUERYING, AND ANALYSIS OF TIME SERIES DATA - 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. | 06-19-2014 |
20140172867 | METHOD FOR STORAGE, QUERYING, AND ANALYSIS OF TIME SERIES DATA - 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. | 06-19-2014 |
20140172868 | SYSTEM AND METHOD FOR STORAGE, QUERYING, AND ANALYSIS SERVICE FOR TIME SERIES DATA - 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. | 06-19-2014 |
20140358968 | METHOD AND SYSTEM FOR SEAMLESS QUERYING ACROSS SMALL AND BIG DATA REPOSITORIES TO SPEED AND SIMPLIFY TIME SERIES DATA ACCESS - 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. | 12-04-2014 |
20140372157 | APPARATUS AND METHOD FOR TIME SERIES DATA ANALYTICS MARKETPLACE - 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. | 12-18-2014 |
20150356154 | SYSTEM FOR STORAGE, QUERYING, AND ANALYSIS OF TIME SERIES DATA - 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. | 12-10-2015 |
20150356485 | METHODS AND SYSTEMS FOR INTELLIGENT EVOLUTIONARY OPTIMIZATION OF WORKFLOWS USING BIG DATA INFRASTUCTURE - Methods and systems for optimizing the configuration and parameters of a workflow using an evolutionary approach augmented with intelligent learning capabilities using a Big Data infrastructure. In an embodiment, a Big Data infrastructure receives workflow input parameters, an objective function, a pool of initial configuration parameters, and completion criteria from a client computer, and then runs multiple instances of a workflow based on the pool of initial configuration parameters resulting in corresponding output results. The process includes storing the workflow input parameters and the corresponding output results, modeling the relationship between changes in the workflow input parameters and the corresponding output results, determining that optimal output results have been achieved, and then transmitting the optimal output and the input-output variable relationships results to the client computer. | 12-10-2015 |