Amazon Technologies, Inc.

Petra Elisabeth Holmes

William Tunstall-Pedoe

David Spike Palfrey

Mihai Valentin Tablan

Andrew Graham Fenn

Arpit Mittal

Sina Samangooei

Dianhuan Lin

Jonathan Gough

Duncan Joseph Reynolds

Gregory Christopher Doran

Meng Li

Mark Edward Rafn

Robert Peter Stacey

Benjamin David Scott

Emilio Fabio Monti

Jianhan Zhu

Andrew Hopkinson

Pedro Ribeiro

Neil Copland

Graham John French

Barry Dean Glennon

Computer implemented systems and methods are described that enable customers to search for a product, and obtain a list of retail locations that are likely to provide that product without any need for any specific information about the stock or products held by that retailer.

Local business and product search system and method

A query parsing system uses a multi-stage process to parse the text of incoming queries before attempting to answer the queries. The multi-stage configuration involves a first trained classifier to determine the query type, or intent, of the text and a plurality of second trained classifiers, where each of the second trained classifiers is configured particularly for one specific respective query type. During query processing, the first trained classifier is used on the text to identify the query type. A second trained classifier for that specific identified query type is then found and used on the text to identify what strings in the text correspond to specific entities needed to resolve the query. The identified text strings and query type are then placed into a form understandable by a knowledge base and sent to the knowledge base for resolution. The classifiers may be trained using queries and answers previously processed by the knowledge base using a rules/template resolution process.

Multi-stage query processing

A voice-controlled question answering system that uses both a knowledge base and a detailed index of other sources that may be accessible over the Internet. The knowledge base is used to answer questions of more general interest whose answers are contained in the knowledge base. The index is used to answer more complex questions that are not answerable using the knowledge base. Web and other sources are analyzed to create the index, where text segments are indexed along with data describing the text segments in a quasi-semantic way. Quasi-semantic features are extracted from incoming spoken questions and used, along with machine learning trained models, to identify an indexed text segment that includes the answer to the question. The text segment may then be rearranged or simply passed to a speech synthesizer so the answer may be spoken aloud to a user.

Quasi-semantic question answering

Techniques are described for adding knowledge to a knowledge base.

Adding to a knowledge base using an ontological analysis of unstructured text

A system and method to recognize and resolve when a source data object is the same or similar to an existing data object in a database using structured information and facts about each object. The system and method compare relations of the source data object and relations of the existing data object in the database and determine how similar the source data object is to the data object in the database based on scores of the comparisons. The system and method may provide outputs, such as whether the data objects match, the data objects are distinct, the source data object is a strong match to multiple data objects in the database, and the data objects conflict one another. The system and method may then resolve the database entries based on the potential matching outputs.

Data object resolver

Techniques are described for adding knowledge to a knowledge base in which alternative information retrieval techniques are used to obtain missing information from an available corpus of documents (e.g., the World Wide Web). Existing relationships in a knowledge base are used to identify entities for which the relationships are not expressed in the knowledge base. The alternative information retrieval techniques are then used to find this information.

Using existing relationships in a knowledge base to identify types of knowledge for addition to the knowledge base

A system and method is disclosed for improving automated question-answering using real-world knowledge from a knowledge base. The system can be used to answer questions from various users. The system can generate answers to these questions using data stored in a knowledge base. In some embodiments, the system is provided with a list of questions separate from any user questions. The system can be trained using these questions in advance of a user question. The system can process the presented questions to determine that it can generate high-quality correct answers. The system can take various steps to determine a high-quality answer to a question. The system can utilize human intelligence providers to improve this process, such as through a human interactive task system. Human intelligence can be used to determine that a question is understood, that a question is answered, and that the answer is of high quality.

Scalable curation system

A system for resolving a user's question regarding media at the user's location where the question includes ambiguity as to the context of the question. Context information is acquired from a device or devices at the user's location, and if multiple possible contexts are identified, the system may attempt to resolve the question for more than one of the possible contexts. The system for answering questions and the source of the media may be different and independent.

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Petra Elisabeth Holmes