Patent application number | Description | Published |
20090077135 | FRAMEWORK FOR HANDLING BUSINESS TRANSACTIONS - Techniques are provided for freeing up resources before operations that change the resources have successfully completed. Resources are freed up by committing database transactions that perform portions of operations before the operations themselves have successfully completed. If the operations fail to complete successfully, then “compensation information” is used to remove the effects of the committed changes that were performed as part of the operation. Techniques are also provided for allowing database transactions to update values without retaining exclusive locks on those values. Operational constraints set forth conditions that must be satisfied before an update is allowed to proceed. If an attempt is made to update a particular value that has changes that may be undone, then the database server determines a plurality of “possible result values” for the particular value. If the possible result values satisfy the operational constraint conditions, then the update is allowed to proceed. | 03-19-2009 |
20100036803 | ADAPTIVE FILTER INDEX FOR DETERMINING QUERIES AFFECTED BY A DML OPERATION - Techniques are disclosed for creating and using a filter index in order to identify registered queries whose result sets are likely to have been changed by changes made to tables. The filter index entries are based on filter conditions. The filter conditions are created based on predicates contained in the registered queries. The filter conditions may include exclusive predicates and join predicates. Join predicates that join a table T | 02-11-2010 |
20130066865 | IMPLICIT OR EXPLICIT SUBSCRIPTIONS AND AUTOMATIC USER PREFERENCE PROFILING IN COLLABORATION SYSTEMS - Systems, methods, and other embodiments associated with event processing are described. In one embodiment, a method includes detecting an event. The example method may also include analyzing the event to extract information about the user and processing a subsequent event in accordance with the extracted information about the user. | 03-14-2013 |
20130066866 | BI-TEMPORAL USER PROFILES FOR INFORMATION BROKERING IN COLLABORATION SYSTEMS - Systems, methods, and other embodiments associated with bi-temporal user profiling are described. An event is detected that occurs at a valid event time. In response to the event, a repository is accessed that stores data describing one or more user profiles that include a profile record valid time period specifying a time at which the given profile record is valid. A prior user profile record is retrieved that has a profile record valid time period that overlaps with the valid event time. An updated user profile record is created based, at least in part, on the event. The updated user profile record is saved with the valid event time demarcating the start of a profile valid time period. The prior user profile with the valid event time demarcating the end of the profile record valid time period is also saved for subsequent processing. | 03-14-2013 |
20140310285 | KNOWLEDGE INTENSIVE DATA MANAGEMENT SYSTEM FOR BUSINESS PROCESS AND CASE MANAGEMENT - Data can be categorized into facts, information, hypothesis, and directives. Activities that generate certain categories of data based on other categories of data through the application of knowledge which can be categorized into classifications, assessments, resolutions, and enactments. Activities can be driven by a Classification-Assessment-Resolution-Enactment (CARE) control engine. The CARE control and these categorizations can be used to enhance a multitude of systems, for example diagnostic system, such as through historical record keeping, machine learning, and automation. Such a diagnostic system can include a system that forecasts computing system failures based on the application of knowledge to system vital signs such as thread or stack segment intensity and memory heap usage. These vital signs are facts that can be classified to produce information such as memory leaks, convoy effects, or other problems. Classification can involve the automatic generation of classes, states, observations, predictions, norms, objectives, and the processing of sample intervals having irregular durations. | 10-16-2014 |
20150106382 | Tables With Unlimited Number Of Sparse Columns And Techniques For An Efficient Implementation - A method and apparatus queries a table in a database where the table includes at least one column declared to be sparse. A binary large object may be used to store the sparse column data. The object includes a column-id and column-value pair for each non-null value. To answer a query with a constraint on a sparse column, the object is searched for one or more column ids to obtain the column values. Rows whose column values match a constraint are returned. In another embodiment, an internal table is used. Each tuple in the internal table has a column id and a value array indexed by an ordinal row number. To answer a query with a constraint on a sparse column, the column value in the internal table is found and matched against the constraint. If the match is successful, the index of the column value in the internal table is returned. | 04-16-2015 |
Patent application number | Description | Published |
20150161899 | METHODS FOR IMPROVING TEST EFFICIENCY AND ACCURACY IN A COMPUTER ADAPTIVE TEST (CAT) - A method for use of pretest items in a test to calculate interim scores is provided. The method includes, for example, a computer implemented test having a plurality of test items that include, for example, a plurality of operational items and one or more pretest items having one or more pretest item parameters. An interim latent construct estimate is calculated using both operational and pretest items. The error for the latent construct estimation is controlled by weighting the contribution of the one or more pretest items. | 06-11-2015 |
20150161900 | METHODS FOR IMPROVING TEST EFFICIENCY AND ACCURACY IN A COMPUTER ADAPTIVE TEST (CAT) - A method for use of pretest items in a test to calculate interim scores is provided. The method includes, for example, a computer implemented test having a plurality of test items that include, for example, a plurality of operational items and one or more pretest items having one or more pretest item parameters. An interim latent construct estimate is calculated using both operational and pretest items. The error for the latent construct estimation is controlled by weighting the contribution of the one or more pretest items. | 06-11-2015 |
20150161901 | METHODS FOR IMPROVING TEST EFFICIENCY AND ACCURACY IN A COMPUTER ADAPTIVE TEST (CAT) - A method for test item selection is provided that includes a computer implemented test battery having at least two or more sections with a plurality of test items. An ability estimate is calculated from an earlier section(s) of the at least two or more sections and an initial item and subsequent items for a subsequent section are selected from the plurality of test items based upon the ability estimate(s) from the earlier section(s). Use of a more informative initial ability estimate in the item selection process can improve interim ability estimation accuracy and item selection efficiency while keeping item exposure and item usage rates at acceptable levels. | 06-11-2015 |
20150161902 | METHODS FOR IMPROVING TEST EFFICIENCY AND ACCURACY IN A COMPUTER ADAPTIVE TEST (CAT) - A method for test item selection is provided that includes a computer implemented test battery having at least two or more sections with a plurality of test items. An ability estimate is calculated from an earlier section(s) of the at least two or more sections and an initial item and subsequent items for a subsequent section are selected from the plurality of test items based upon the ability estimate(s) from the earlier section(s). Use of a more informative initial ability estimate in the item selection process can improve interim ability estimation accuracy and item selection efficiency while keeping item exposure and item usage rates at acceptable levels. | 06-11-2015 |