Teradata Us, Inc.

Harold R Lee

Michael Chaves

Jason Keith Figge

Scott Shelton

Dennis Tackett

Henry Fu

Anish Shah

Joshua David Anderson

Rajeswara Rao Kottu

Sean Pritchard

Jeffrey Canna

Alex Chapman

Ara Yapejian

Anil Peres-da-Silva

Steven Kennedy

A sentiment-scoring system may include a storage device configured to store a plurality of keywords, keyword groups, and a keyword group hierarchy. Each keyword may be associated with at least one of the keyword groups. The keyword hierarchy may include a hierarchy associated with each keyword group. The system may further include a processor in communication with the storage device. The processor may be configured to locate a plurality of sentiment expressions and identify a plurality of keywords present in the plurality of sentiment expressions. The processor may be further configured to determine at least one respective keyword group associated with each identified keyword and determine a sentiment score for each sentiment expression with respect to the associated keyword group within the keyword hierarchy. The processor may be further configured to provide at least one sentiment score to a display. A method and computer-readable medium may also be implemented.

Sentiment expression analysis based on keyword hierarchy

The subject mater herein relates to requesting data from a database and, more particularly, to database query table substitution. Various embodiments provide systems, methods, and software to evaluate requests for data from a database and make table substitutions in the request to reduce a number of tables queried. Some embodiments include receiving a data request including data from two or more database table columns and building a list of all database tables specified in the data request. Some such embodiments further include, for each column in the data request, identifying each table from the list of all tables within which the column is present and identifying a least number of one or more tables that together include all of the columns of the data request. The data request may then be modified by changing the table of one or more of the columns in the received data requests.

Database query table substitution

Techniques are presented for synchronizing data store tables. Elements of first tables are linked together to form dependent chains. The dependencies are not housed with the elements in the first tables; rather, the dependencies are housed in multiple second tables. Each second table maps one of the elements from one of the first tables to another of the elements in another of the first tables.

Techniques for synchronizing data store tables

Techniques are presented for mapping a physical table to multiple virtual tables. One or more fields within a results set from a query are mapped or associated to one or more virtual tables. The virtual tables are organized as sub graphs and connected together as a set. A reference to the set is provided to a table join analysis service and a join is performed against the set to produce a single logical reference to a table. The single table reference may be treated as a single table for purposes of subsequent search and retrieval by a searcher.

Techniques for mapping a physical table to multiple virtual tables

Techniques are presented for reusing business measures within a data store. A measure is associated with a measure type. Each measure is associated with a particular data store schema or schema element and includes metadata for fields and calculations against those fields. Requestors can select existing measures, create new measures, delete existing measures, and/or modify existing measures. A measure, when processed against the data store, produces results from a data store that are associated with the data store schema or the schema element and which conform to the fields and calculations defined within the measure's metadata.

Reusable measures

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Holly Springs, NC, United States of America

Harold R Lee