Abstract:
Associating job responsibilities with job titles is described. A database system identifies a job level and a job department associated with a job title stored by an object. The database system identifies level-based job responsibilities associated with the job level. The database system identifies department-based job responsibilities associated with the job department. The database system identifies at least one job responsibility associated with the job title based on the level-based job responsibilities and the department-based job responsibilities. The database system stores each identified job responsibility in metadata and/or a field associated with the object. The database system outputs a message based on the object to a user device, in response to a search that specifies any identified job responsibility.
Abstract:
Prioritizing accounts in user account sets is described. A system creates an accounts profile for a set of accounts based on multiple attributes associated with each account of the set of accounts. The system calculates multiple account scores corresponding to multiple accounts, based on comparing multiple attributes associated with each of the multiple accounts against the accounts profile, wherein the set of accounts includes the multiple accounts. The system orders the multiple accounts based on the corresponding multiple account scores. The system recommends for a user associated with the set of accounts to prioritize work on the multiple accounts based on the order of the multiple accounts.
Abstract:
A system determines a first volume of out-calls of a first out-call type made by a software container that is executing an application during a time period. The system determines a second volume of out-calls of a second out-call type made by the software container. The system determines a first ratio of the first volume to a combined volume of out-calls of all out-call types made by the software container. The system determines a second ratio of the second volume to the combined volume of out-calls of all out-call types made by the software container. The system determines a measure by comparing the first ratio to a third ratio associated with the first out-call type, and by comparing the second ratio to a fourth ratio associated with the second out-call type. The system identifies any behavior or any application type associated with the application, based on the measure.
Abstract:
A system identifies a first number of distinct values stored in a first field by a dataset of records. The system identifies a second number of distinct values stored in a second field by the dataset of records. The system creates a trie from values stored in a field by multiple records, the field corresponding to the first field or the second field, based on comparing the first number to the second number. The system associates a node in the trie with one of the multiple records, based on a value stored in the field by the record. The system identifies a branch sequence in the trie as a key for a prospective record, based on a prospective value stored in a corresponding field by the prospective record. The system uses the key for the prospective record to identify one of the multiple records that matches the prospective record.
Abstract:
Some embodiments of the present invention include a method for determining duplicate records in multiple objects and may include combining records associated with a first object with records associated with a second object to generate a third object, wherein the first object is related to the second object; performing de-duplication on the third object to generate a combined group of duplicate sets; and from the combined group of duplicate sets, identifying at least one duplicate set associated with both the first object and the second object based on the duplicate set having at least one record associated with the first object and at least one record associated with the second object.
Abstract:
Some embodiments of the present invention include a method for determining a dense subset from a group of records using a graphical representation of the group of records, the graphical representation having nodes and edges, a node associated with a record from the group of records, an edge connecting two nodes associated with two related records, wherein a node is associated with a weight corresponding to a number of edges connected to the node, wherein a record is added to the dense subset based on its associated node having a highest weight and a density that satisfies a density threshold, the density being based on the content of the dense subset, and wherein the content of the dense subset is to be processed as including duplicate records.
Abstract:
Some embodiments of the present invention include a system and method for removing duplicate records from a group of records in a database system. The method includes generating a first cluster of records from the group of records, generating a second cluster of records from the group of records, identifying sets of duplicate records in the first cluster of records, and identifying sets of duplicate records in the second cluster of records. The method also includes merging at least two sets of duplicate records associated with both the first cluster and the second cluster of records to form a merged set of duplicate records. The merging is performed based on the at least two sets of duplicate records having a common record. Duplicate records in the group of records may then be removed by removing duplicate records from the merged set of duplicate records.
Abstract:
A system and method for mapping columns from a source file to a target file. The header for each source column is evaluated heuristically to see if the header matches a predefined entity. The contents of a group of cells in the source column are evaluated probabilistically to determine a probability that the cell contents correspond to at least one of the predefined entities. A score is assigned to the likelihood that the column corresponds to one or more predefined entities. If the score meets a threshold, then the correspondence between the source column and one or more predefined entities is mapped. If the score fails to meets the threshold, then the correspondence between the source column and one or more undefined entities is mapped. Finally, each source column is transformed into a target column in accord with the map.