Abstract: Semantic analysis to resolve ambiguous user input data with respect to a request for data includes identifying tokens based on the text string, identifying a tables in a database, wherein a token indicates a column from a table and a token indicates a column from another table, identifying candidate join paths for joining tables, obtaining respective candidate results using the candidate join paths, outputting combined candidate results including values from the respective candidate results, obtaining second user input data indicating a selected value, identifying the request for data as unambiguous and identifying a selected join path based on the selected value, and, in response to identifying the request for data as unambiguous, outputting data responsive to the request for data using the selected join path.

Abstract: Semantic analysis to resolve ambiguous user input data with respect to a request for data includes identifying tokens based on the text string, identifying a tables in a database, wherein a token indicates a column from a table and a token indicates a column from another table, identifying candidate join paths for joining tables, obtaining respective candidate results using the candidate join paths, outputting combined candidate results including values from the respective candidate results, obtaining second user input data indicating a selected value, identifying the request for data as unambiguous and identifying a selected join path based on the selected value, and, in response to identifying the request for data as unambiguous, outputting data responsive to the request for data using the selected join path.

Abstract: Semantic analysis to resolve ambiguous user input data with respect to a request for data includes identifying tokens based on the text string, identifying a tables in a database, wherein a token indicates a column from a table and a token indicates a column from another table, identifying candidate join paths for joining tables, obtaining respective candidate results using the candidate join paths, outputting combined candidate results including values from the respective candidate results, obtaining second user input data indicating a selected value, identifying the request for data as unambiguous and identifying a selected join path based on the selected value, and, in response to identifying the request for data as unambiguous, outputting data responsive to the request for data using the selected join path.

Abstract: Semantic analysis to resolve ambiguous user input data with respect to a request for data includes identifying tokens based on the text string, identifying a tables in a database, wherein a token indicates a column from a table and a token indicates a column from another table, identifying candidate join paths for joining tables, obtaining respective candidate results using the candidate join paths, outputting combined candidate results including values from the respective candidate results, obtaining second user input data indicating a selected value, identifying the request for data as unambiguous and identifying a selected join path based on the selected value, and, in response to identifying the request for data as unambiguous, outputting data responsive to the request for data using the selected join path.

Abstract: Token based dynamic data indexing with integrated security includes generating attribute tokens based on a database, each attribute token including an ordered sequence of symbols, generating an index indexing the attribute tokens, such that the index includes a root node, a first branch depending from the root node representing a first symbol from a first attribute token, and a security bitmask for the first attribute token, such that a security bitmask for the first branch at the root node is a hierarchical logical disjunction based on the security bitmask for the first attribute token, such that generating a response receiving an information retrieval request indicating a search symbol and a search context, is based on a determination that a horizontal logical disjunction of a vertical logical conjunction of the security bitmask for the first branch and a security bitmask for the information retrieval request indicates authorization.

Abstract: A search engine performs semantic analysis of unstructured search terms to generate relational database queries. By understanding the semantics, the search engine more effectively identifies and predicts what information the user is searching for and provides more in-depth user assistance. The search engine uses different ranking schemes to identify which data is most likely associated with search terms and provides both row level and object level data security. The search engine may identify ambiguous search requests and allows the user to select different join paths that create different mappings between the data. The search engine may generate worksheets containing the selected mappings.

Abstract: A search engine performs semantic analysis of unstructured search terms to generate relational database queries. By understanding the semantics, the search engine more effectively identifies and predicts what information the user is searching for and provides more in-depth user assistance. The search engine uses different ranking schemes to identify which data is most likely associated with search terms and provides both row level and object level data security. The search engine may identify ambiguous search requests and allows the user to select different join paths that create different mappings between the data. The search engine may generate worksheets containing the selected mappings.