ANALYTIC SOLUTION WITH A SELF-LEARNING AND CONTEXT-SENSITIVE SEMANTIC LAYER
First Claim
1. A system for dynamic data modeling that enables a self-learning and context-sensitive semantic layer to query data, the system comprising:
- at least one processor;
a non-transitory computer-readable medium configured to store executable instructions that when executed by the at least one processor are configured to implement;
a query engine configured to receive a query from a user via a user interface layer for obtaining data from one or more databases, determine if a keyword of the query can be mapped to at least one of a plurality of keyword mappings stored in a semantic layer, and if the keyword cannot be mapped, provide an interactive object, via the user interface layer, to learn a new keyword mapping for the keyword such that the semantics layer is updated with the new keyword mapping for future queries; and
a prediction engine configured to check for previous queries of the user or other users that map the query to predict a next query,the query engine configured to provide query results of the query and the next query as a suggestion via the user interface layer.
1 Assignment
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Accused Products
Abstract
According to a general aspect, a system includes a query engine configured to receive a query from a user via a user interface layer for obtaining data from one or more databases, determine if a keyword of the query can be mapped to at least one of a plurality of keyword mappings stored in a semantic layer, and if the keyword cannot be mapped, provide an interactive object, via the user interface layer, to learn a new keyword mapping for the keyword such that the semantics layer is updated with the new keyword mapping for future queries. The system includes a prediction engine configured to check for previous queries of the user or other users that map the query to predict a next query, and the query engine is configured to provide query results of the query and the next query as a suggestion via the user interface layer.
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Citations
20 Claims
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1. A system for dynamic data modeling that enables a self-learning and context-sensitive semantic layer to query data, the system comprising:
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at least one processor; a non-transitory computer-readable medium configured to store executable instructions that when executed by the at least one processor are configured to implement; a query engine configured to receive a query from a user via a user interface layer for obtaining data from one or more databases, determine if a keyword of the query can be mapped to at least one of a plurality of keyword mappings stored in a semantic layer, and if the keyword cannot be mapped, provide an interactive object, via the user interface layer, to learn a new keyword mapping for the keyword such that the semantics layer is updated with the new keyword mapping for future queries; and a prediction engine configured to check for previous queries of the user or other users that map the query to predict a next query, the query engine configured to provide query results of the query and the next query as a suggestion via the user interface layer. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. A computer program product tangibly embodied on a non-transitory computer-readable storage medium and including executable code that, when executed, is configured to cause at least one processor to:
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receive a query from a user for obtaining data from one or more databases; determine if a keyword of the query can be mapped to at least one of a plurality of keyword mappings stored in a semantic layer; if the keyword cannot be mapped, provide an interactive object, via the user interface layer, to learn a new keyword mapping for the keyword; update the semantics layer with the new keyword mapping for future queries; check for previous queries of the user or other users that map the query to predict a next query; and display query results of the query and the next query to the user via the user interface layer. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17)
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18. A method for dynamic data modeling that enables a self-learning and context-sensitive semantic layer to query data, the method being performed by at least one processor, the method comprising:
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receiving a query from a user for obtaining data from data sources, the query including a first keyword and a second keyword; determining that the first keyword is a new keyword but is similar to a known keyword mapping stored in a semantic layer; determining that the second keyword cannot be mapped to any known keyword mappings stored in the semantic layer; providing an interactive object, via a user interface layer, to request a new keyword mapping for the second keyword; updating the semantics layer with the new keyword mapping for future queries; and obtaining query results corresponding to the query having the first keyword and the second keyword; and displaying the query results via the user interface layer. - View Dependent Claims (19, 20)
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Specification