Company Filing History:
Years Active: 2021-2025
Title: Alonzo Canada: Innovator in Natural Language Processing
Introduction
Alonzo Canada is a notable inventor based in Menlo Park, CA. He has made significant contributions to the field of natural language processing, holding a total of 3 patents. His work focuses on enhancing database query systems through innovative techniques.
Latest Patents
Alonzo's latest patents include advancements in natural language question answering systems. One of his patents describes a method for identifying a current set of context features for a database query associated with a string. This involves selecting an inference record from an inference store based on a comparison of context features. The database query is then modified using the resolution of the inference record to obtain an inferred database query, which is used to invoke a search of a database for results.
Another patent outlines a search interface for a database that receives string data from a user interface. This process includes determining a sequence of tokens representative of the string data through natural language processing. A first database query is generated, and feedback data is received to modify the sequence of tokens, leading to a second database query that retrieves results from the database.
Career Highlights
Alonzo Canada is currently employed at ThoughtSpot, Inc., where he continues to develop innovative solutions in the realm of data querying and natural language processing. His work has positioned him as a key figure in the advancement of user-friendly database interactions.
Collaborations
Alonzo collaborates with talented individuals such as Amit Prakash and Ravi Tandon, contributing to a dynamic team focused on pushing the boundaries of technology in their field.
Conclusion
Alonzo Canada's contributions to natural language processing and database query systems highlight his innovative spirit and dedication to improving technology. His patents reflect a commitment to enhancing user experience and efficiency in data retrieval.