International Business Machines Corporation

Mindbridge Analytics Inc.

Robin Neil Grosset

Yu Zou

Mohsen Rais-Ghasem

Jose Vazquez

David Hood

Graham A Watts

Qing Wei

David B Cushing

Martin Petitclerc

Nicolas Yvon Elijah Milligan

Corey Matthew Yanofsky

Michael Thomas Smith

Wing-Leung Chan

Pierre Iorio

Gregoire D Lanthier

John C Griggs

Charles Ng

Ramon L H Pisters

Franciscus J J Van Ham

Antonius G P Steijvers

Joachim Limburg

The present invention discloses numerous implementations of system and method which receives a user request and, using methods of natural language processing including part of speech tagging, analyses the user request to generate a query to a database of information. Based on the machine understanding, the system presents an interactive representation of the uttered request back to the user. This provides context to the user, which explains the machine understanding of the request and acts as an interface to iteratively refine or adjust the machine understanding by altering specific elements of the uttered language. The methods of altering specific elements of the uttered language may vary depending on the element and a variety of user selectable interfaces may be used to display one or more queried elements along with alternative elements pertaining to the queried element. The user could select an alternative element and change the database query.

Method and system for presenting a user selectable interface in response to a natural language request

Methods are provided for semantic processing of data files including detecting formats of data embedded in the data files and converting the data to formats compatible with a data analysis tool. The method may comprise determining if the data file comprises signature characteristics associated with a known data format and, if so, determining a set of data manipulation operations associated with the known data format to convert the data file to a compatible format for the data analysis tool. The method may further comprise semantically analyzing components of the data files to assess formatting across a required set of criterions needed by the data analysis tool and determining sets of data manipulation operations to perform to convert the data file to a compatible format.

Method and apparatus for shaping data using signature recognition

Methods are provided for semantic processing of data files including detecting formats of data embedded in the data files and converting the data to formats compatible with a data analysis tool. The method may comprise semantically analyzing components of the data files to assess formatting across a required set of criterions needed by the data analysis tool and determining sets of data manipulation operations to perform to convert the data file to a compatible format. Semantic analysis of values in criterions across data entries may allow for groups of entries to be associated together with transaction ID values common to and unique to the groups of entries associated with a common transaction. The method may group data entries based on values in criterions, test potential groupings based on a behavior test to assess characteristics of entries when grouped in the proposed manner, and generate a new transaction ID criterion in each of the data entries.

Method and apparatus for shaping data using semantic understanding

A computing device may receive a natural language query. The computing device may determine, based on the natural language query, a set of search criteria. The computing device may determine, from a plurality of data sets, two or more data sets that are relevant to the natural language query based at least in part on matches between the set of search criteria and attributes of the plurality of data sets. The computing device may join the two or more data sets, including joining one or more rows and one or more columns of the two or more data sets to produce a joint data set. The computing device may output a representation of the joint data set.

Search-based detection, link, and acquisition of data

A computing device receives a natural language query. The computing device determines, based on the natural language query, a set of search criteria. The computing device determines, from a plurality of data sets, two or more data sets that are relevant to the natural language query based at least in part on matches between the set of search criteria and attributes of the plurality of data sets. The computing device joins the two or more data sets, including joining one or more rows and one or more columns of the two or more data sets to produce a joint data set. The computing device outputs a representation of the joint data set.

Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes comparing, with one or more computing devices, a data item heading from the data source with concept keywords in a concept library, the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts. The method further includes identifying, with one or more computing devices, one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library. The method further includes identifying, with one or more computing devices, the data item heading as being associated with the particular concept.

Business intelligence data models with concept identification using language-specific clues

A processor-implemented method retrieves information from a database system. A data query, which includes a specification of information to be retrieved from the database system, is generated. A first parameter specifying a condition to be met by the retrieved information is defined. A second parameter specifying one or more data reduction operations to be executed if the condition defined by the first parameter is not met is defined. The generated data query and the first and second parameters are then transmitted to the database system.

Information retrieval from a database system

A system provides multidimensional tuple Hilbert ordering within a linear storage structure to enable more consistent and efficient access to stored multidimensional tuples. The database system comprises a tuple storage module that receives multidimensional data elements, where each multidimensional data element is defined by a plurality of different object types, and where each object is associated with a different dimension within a multidimensional data space. The tuple storage module further forms a respective tuple for each of the multidimensional data elements by mapping each object to an associated reference and applies a Hilbert function to the references of each of the tuples to determine a respective Hilbert ordering for each of the tuples. The system further comprises a linear data storage structure that includes a B-tree for storing the Hilbert ordering.

Hilbert ordering of multidimensional tuples within computing systems

Provided are techniques for processing a multidimensional query. For each multidimensional expression in the multidimensional query, the multidimensional expression is evaluated to generate a representation that includes an evaluation context, a degeneration status, and condensed value storage that does not store data that would be replicated due to degeneration, and the representation is stored.

Encapsulation of multiplicity and sparsity in multidimensional query execution systems

A secure caching system and caching method include receiving a user request for data, the request containing a security context, and searching a cache for the requested data based on the user request and the received security context. If the requested data is found in cache, returning the cached data in response to the user request. If the requested data is not found in cache, obtaining the requested data from a data source, storing the obtained data in the cache and associating the obtained data with the security context, and returning the requested data in response to the user request. The search for the requested data can include searching for a security list that has the security context as a key, the security list including an address in the cache of the requested data.

Optimizing data cache when applying user-based security

An enterprise business intelligence system includes a data access service. In one example, a method comprises receiving, with a data access service, a query and a report specification from an application, wherein the data access service is positioned between the application and a data source; creating a run tree that comprises a sequence of executable decoration nodes; executing the query on the data source, thereby providing a query result set comprising query results drawn from the data source that are responsive to the query; and executing the sequence of decoration nodes on the query result set. The decoration nodes modify the query result set, thereby producing a decorated result set based on the query result set and the decoration nodes. Producing the decorated result set comprises associating members or values in the query results with corresponding positions or calculated members in the report specification.

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Ottawa, Canada

Robin Neil Grosset