Thoughtspot, Inc.

Ajeet Singh

Amit Prakash

Shashank Gupta

Satyam Shekhar

Shikhar Agarwal

Shailesh Chauhan

Rakesh Kothari

Amitabh Singhal

Ravi Tandon

Ashish Shubham

Aditya Viswanathan

Pavan Ram Piratla

Alonzo Canada

Maneesh Apte

Manikanta Balakavi

Sanjay Agrawal

Manikanta Venkata Rahul Balakavi

Abhishek Rai

Priyendra Singh Deshwal

Vijay Krishnan Ganesan

Vibhor Nanavati

Stephane Antonin Kiss

Joy Dutta

Shikhar Agrawal

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.

Token based dynamic data indexing with integrated security

A current set of context features for a database query that is associated with a string is identified. The database query includes a sequence of tokens of a database syntax, and the current set of context features includes words from the string and tokens from the database query. An inference record is selected from an inference store based on a comparison of the current set of context features to context features of inference records in the inference store. The database query is modified using a resolution of the inference record to obtain an inferred database query. The resolution includes one or more tokens of the database syntax. A search of a database is invoked using a query based on the inferred database query to obtain search results.

Natural language question answering systems

Providing a search interface for a database includes receiving string data entered via a user interface. A sequence of tokens representative of the string data is determined. Determining the sequence of tokens includes applying natural language processing to the string data. A first database query is generated in accordance with the sequence of tokens. Respective text representations for tokens in the sequence of tokens are presented via the user interface. Feedback data related to the sequence of tokens is received via the user interface. A token of the sequence of tokens is modified based on the feedback data to obtain a modified sequence of tokens. A second database query is generated based on the modified sequence of tokens. Results data are obtained from the database responsive to execution of the second database query by the database. Data based on the results data are output for presentation in the user interface.

Systems and methods for natural language question answering are described. For example, methods may include determining a set of candidate database queries, including respective sequences of tokens of a database syntax, based on a string; determining a first score for a first candidate database query from the set of candidate database queries, wherein the first score is based on a match between one or more words of the string and a token of the respective sequence of tokens of the first candidate database query; determining a second score for the first candidate database query, wherein the second score is based on natural language syntax data determined for words of the string; selecting, based on the first score and the second score, the first candidate database query from the set of candidate database queries; and invoking a search of the database using the first candidate database query to obtain search results.

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.

An information retrieval system converts unstructured ad-hoc search queries into structured search instructions that retrieve data in a structured relational database or an unstructured database. Data from the database is uploaded into a distributed in-memory database system. Tokens are automatically generated based on attributes, measures, and other metadata extracted from the relational database. The tokens are then compared with the non-structured ad-hoc user search queries. The information retrieval system uses the tokens to identify or predict what structured data is associated with user search queries. The tokens guide the user through a set of search terms that the system then uses to generate the structured query instructions. The structured query instructions retrieve specific data and answers from in the database system.

Information retrieval system

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Saratoga, CA, United States of America

Ajeet Singh