Patent application number | Description | Published |
20110153589 | DOCUMENT INDEXING BASED ON CATEGORIZATION AND PRIORITIZATION - Disclosed are methods and systems for improving indexing throughput. The methods and systems involve receiving one or more documents for indexing, categorizing the one or more documents based on a document type, a document size and a processing priority, assigning buckets to the categorized one or more documents according to the document type, the document size and the processing priority and scheduling the buckets for processing based on a document type priority, a bucket type and number of threads available to process the buckets. | 06-23-2011 |
20120078859 | SYSTEMS AND METHODS TO UPDATE A CONTENT STORE ASSOCIATED WITH A SEARCH INDEX - Some aspects include determination of second document identifiers added to a search index. The search index associates each of a plurality of words with at least one of a plurality of first document identifiers. For each of the second document identifiers, metadata of a document identified by the second document identifier is added to a content store storing metadata of each document identified by the plurality of first document identifiers. | 03-29-2012 |
20120331447 | ADAPTIVE CHANGE MANAGEMENT IN COMPUTER SYSTEM LANDSCAPES - An adaptive automatic change management for computer system landscapes is described herein. A predefined set of attributes are extracted or obtained for a computer system artifact, together with a number of values assigned to the set of attributes. A unique identification section is created and distributed among the computer systems in the landscape based on the set of attributes and the assigned values, where the unique identification section encompass computer system artifacts of a same kind. A modification of an artifact of the same kind is tracked at a computer system. The tracked modification is automatically applied in the computer system to one or more incoming computer system artifacts of the same kind. | 12-27-2012 |
20130166573 | Managing Business Objects Data Sources - Methods, computer-readable media, and systems for managing business objects data sources. A search query that includes multiple query terms is received. Each query term at least partially represents metadata associated with one of multiple business objects data sources that each stores multiple data items. Multiple search index documents are searched to identify one or more business objects data sources that are each associated with metadata at least partially represented by each query term. Multiple metadata tables are searched to identify metadata associated with each identified business objects data source. The identified business objects data sources are searched for data items that satisfy the identified metadata. Representations of the data items and the metadata are provided in response to receiving the search query. | 06-27-2013 |
20130166598 | Managing Business Objects Data Sources - Methods, non-transitory computer-readable media, and systems for managing business objects data sources. Multiple business objects data sources, each storing multiple data items, are accessed. For each data source, multiple computer-searchable index documents and multiple metadata tables, including master tables and mapping tables, are generated. The multiple computer-searchable index documents and the multiple metadata tables are provided to perform a search for data items in the multiple business objects data sources. | 06-27-2013 |
20130218893 | EXECUTING IN-DATABASE DATA MINING PROCESSES - Various embodiments of systems and methods for executing in-database data mining processes are described herein. In one aspect, the method includes identifying a newly created chain comprising a plurality of components connected together to perform a data mining task, generating an identifier (ID) for the newly created chain, identifying metadata associated with the chain, and storing the ID and the metadata related to the newly created chain into a repository. Each component comprises a parameterized script including one or more parameters. Values of the parameters are stored in the repository. The parameters within the scripts are replaced by their corresponding values and the components of the chain are executed sequentially to generate a final output. | 08-22-2013 |
20140067457 | WORKFLOW EXECUTION FRAMEWORK - A workflow execution framework is generated to execute a received workflow. The workflow is semantically analyzed to determine workflow chain and associated workflow components. To execute the workflow chain, a terminal component in the workflow chain and a corresponding sequential hierarchy of the workflow components are detected. A result descriptor of a data source component corresponding to the terminal component is computed and stored in an execution state table. Result descriptors are computed for the workflow components succeeding the data source component in the sequential hierarchy and are stored in the execution state table. Upon detecting a dataflow between the data source component and one of the succeeding workflow components, data along each row of the execution state table is extracted to process the one of the succeeding workflow components. The workflow is executed by processing the workflow components associated with the workflow chain, thereby executing the workflow chain. | 03-06-2014 |
20140067874 | PERFORMING PREDICTIVE ANALYSIS - Various embodiments of systems and methods for performing predictive analysis are described herein. In one aspect, the method includes receiving a command for publishing a chain comprising a plurality of components connected together to perform predictive analysis. Based upon the command, a plurality of procedures corresponding to the plurality of components of the chain is generated. The generated procedures are integrated according to an order of connectivity of the components within the chain. A database object including the integrated procedures is generated. The database object is stored within a database. The stored database object is executable for performing predictive analysis. | 03-06-2014 |
20140125673 | PRESENTING DATA RECORDS BASED ON BINNING AND RANDOMIZATION - In one embodiment, data records associated with attributes are received. A check is made to determine whether the data records are greater than a maximum data record limit of a graph. Further, when the maximum number of data records in the bin is less than or equal to the maximum data record limit of the graph, the data records are retrieved and presented in the graph. When the data records are greater than the maximum data record limit of the graph, the data records are grouped into bins based on initial bin sizes corresponding to the plurality of attributes. Furthermore, weighted densities of the bins are determined using a maximum number of data records associated with a bin and a maximum data record limit of the bin. Further, the graph is rendered to present the weighted densities of the bins using a randomization technique to analyze the data records. | 05-08-2014 |
20140156649 | Automatic Detection of Patterns and Inference in a Dataset - Techniques allow automatic identification of statistically significant attribute combinations in a dataset, and provide users with an understanding thereof including starting points for further analysis. Statistically significant combinations may be obtained from large data sets by limiting combinations to four or fewer attributes. The combinations obtained may be ranked to differentiate patterns, e.g. according to factors such as error ratio, decision tree depth, occurrences, and number of attributes. Still further insights may be achieved by ranking attributes according to the number of statistically significant combinations in which they appear. For useful visualization of statistically significant information within the patterns, only those having at least one measure/numeric may analyzed for further insight (e.g. by an outlier algorithm) and presented as output in a chart (e.g. pie, bar) form. The decision tree approach of various embodiments may facilitate ‘What if’ analysis of the data, as well as obtaining the reverse inference. | 06-05-2014 |
20140304263 | IN-DATABASE PROVISIONING OF DATA - A user uploads date sets through a client to a database. The data sets are provisioned in the database for in-database searching. The data sets are evaluated and classifications for the columns of the tables that include the data set are detected. Columns content may be classified into different analysis types, aggregation types, formats, categories, hierarchies, etc. Metadata is generated based on the evaluation of the data sets. A schema is used to store the metadata that describes the detected classification of the columns. The schema is stored in the database and is used when a search in the database is performed. | 10-09-2014 |