Abstract: Systems and methods are disclosed herein for processing a natural language query on data tables. According to some embodiments, a query term is obtained from a natural language query. A table summary is prepared based on the query term and a formula of the natural language query is generated based on the table summary. A result is generated based on the formula. Responsive to receiving negative feedback to the result, one or more of the table summary or the formula is disassociated from the query term.

Abstract: Systems and methods are disclosed herein for processing a natural language query on data tables. According to some embodiments, a natural language query may be originated by a user via a user interface. The natural language query may be parsed to obtain a query term, and a grid range may be identified in a data table as relevant to the query term. A table summary may be prepared including a plurality of characteristics based on the grid range. A logic operation may then be determined to apply on the plurality of characteristics to derive the query term. The logic operation may then be translated into a formula executable on the data table, and the formula is applied on the data table to generate a result in response to the natural language query.

Abstract: Systems and methods are disclosed herein for processing a natural language query on data tables. According to some embodiments, a natural language query may be originated by a user via a user interface. The natural language query may be parsed to obtain a query term, and a grid range may be identified in a data table as relevant to the query term. A table summary may be prepared including a plurality of characteristics based on the grid range. A logic operation may then be determined to apply on the plurality of characteristics to derive the query term. The logic operation may then be translated into a formula executable on the data table, and the formula is applied on the data table to generate a result in response to the natural language query.

Abstract: Systems and methods are disclosed herein for processing a natural language query on data tables. According to some embodiments, a natural language query may be originated by a user via a user interface. The natural language query may be parsed to obtain a query term, and a grid range may be identified in a data table as relevant to the query term. A table summary may be prepared including a plurality of data entities based on the grid range. A logic operation may then be determined to apply on the plurality of data entities to derive the query term. The logic operation may then be translated into a formula executable on the data table, and the formula is applied on the data table to generate a result in response to the natural language query.

Abstract: Systems and methods are disclosed herein for processing a natural language query on data tables. According to some embodiments, a natural language query may be originated by a user via a user interface. The natural language query may be parsed to obtain a query term, and a grid range may be identified in a data table as relevant to the query term. A table summary may be prepared including a plurality of data entities based on the grid range. A logic operation may then be determined to apply on the plurality of data entities to derive the query term. The logic operation may then be translated into a formula executable on the data table, and the formula is applied on the data table to generate a result in response to the natural language query.

Abstract: A server may receive an article that is retrieved from a server; determine whether the article satisfies first criteria based on content of the first article; annotate the article with a first article type when the article satisfies the first criteria; determine whether the article satisfies second criteria based on information associated with the article; annotate the article with a second article type when the article satisfies the second criteria; and store the article in association with a topic and at least one of the first article type or the second article type. The different server may be associated with a news website.

Abstract: A server may receive an article that is retrieved from a server; determine whether the article satisfies first criteria based on content of the first article; annotate the article with a first article type when the article satisfies the first criteria; determine whether the article satisfies second criteria based on information associated with the article; annotate the article with a second article type when the article satisfies the second criteria; and store the article in association with a topic and at least one of the first article type or the second article type. The different server may be associated with a news website.

Abstract: The invention concerns a detection of duplicate tuples in a database. Previous domain independent detection of duplicated tuples relied on standard similarity functions (e.g., edit distance, cosine metric) between multi-attribute tuples. However, such prior art approaches result in large numbers of false positives if they are used to identify domain-specific abbreviations and conventions. In accordance with the invention a process for duplicate detection is implemented based on interpreting records from multiple dimensional tables in a data warehouse, which are associated with hierarchies specified through key—foreign key relationships in a snowflake schema. The invention exploits the extra knowledge available from the table hierarchy to develop a high quality, scalable duplicate detection process.

Abstract: The invention concerns a detection of duplicate tuples in a database. Previous domain independent detection of duplicated tuples relied on standard similarity functions (e.g., edit distance, cosine metric) between multi-attribute tuples. However, such prior art approaches result in large numbers of false positives if they are used to identify domain-specific abbreviations and conventions. In accordance with the invention a process for duplicate detection is implemented based on interpreting records from multiple dimensional tables in a data warehouse, which are associated with hierarchies specified through key-foreign key relationships in a snowflake schema. The invention exploits the extra knowledge available from the table hierarchy to develop a high quality, scalable duplicate detection process.

Abstract: The invention concerns a detection of duplicate tuples in a database. Previous domain independent detection of duplicated tuples relied on standard similarity functions (e.g., edit distance, cosine metric) between multi-attribute tuples. However, such prior art approaches result in large numbers of false positives if they are used to identify domain-specific abbreviations and conventions. In accordance with the invention a process for duplicate detection is implemented based on interpreting records from multiple dimensional tables in a data warehouse, which are associated with hierarchies specified through key—foreign key relationships in a snowflake schema. The invention exploits the extra knowledge available from the table hierarchy to develop a high quality, scalable duplicate detection process.

Abstract: The invention concerns a detection of duplicate tuples in a database. Previous domain independent detection of duplicated tuples relied on standard similarity functions (e.g., edit distance, cosine metric) between multi-attribute tuples. However, such prior art approaches result in large numbers of false positives if they are used to identify domain-specific abbreviations and conventions. In accordance with the invention a process for duplicate detection is implemented based on interpreting records from multiple dimensional tables in a data warehouse, which are associated with hierarchies specified through key—foreign key relationships in a snowflake schema. The invention exploits the extra knowledge available from the table hierarchy to develop a high quality, scalable duplicate detection process.