Google Inc.

Sabin, Robert

Amit Singhal

Paul Haahr

Simon Tong

Steven D Baker

Uri N Lerner

Krishna Asur Bharat

John Ogden Lamping

Paul A Tucker

Eric G Jackson

Mehran Sahami

David Robert Bailey

Adam Douglas Smith

Monika Hildegard Henzinger

Daniel Trawick Egnor

Jun Wu

Jonathan James Effrat

Matt Cutts

Xianping Ge

Mizuki McGrath

Marcin Kaszkiel

Elizabeth Hamon

Abhishek Parmar

Ben Gomes

Mizuki Mcgrath

Stephen R Lawrence

Robert Sabin

Steve Lawrence

Jack Wright Menzel

Vineet Gupta

Urs Hoelzle

James Robert Muller

Arvind Sivaram Sharma

Srikrishnan Subramanian

Jordan Jozwiak

Michael Ng

Dev M Patel

Johnathan J Effrat

Yao Lin

Martin Kaszkiel

Rasika S Kumar

Jacqueline Frances Bavaro

Eugene Nudelman

Ganesh Skandan

Implementations described herein relate to determining how an automated assistant should respond to a given spoken utterance received in a vehicular environment to enforce consistency between value(s) and/or unit(s) that are displayed at a given display device of an in-vehicle computing device and value(s) and/or unit(s) that are utilized in executing a given vehicular command or that are provided for presentation to a user in response to a given vehicular request. For example, implementations can receive the given spoken utterance, identify the given vehicular command/request based on processing the given spoken utterance, and determine an original equipment manufacturer (OEM) query based on the given vehicular command/request included in the spoken utterance, and transmit the OEM query to a given OEM component. Further, implementations can determine how the automated assistant should respond to the given spoken utterance based on responsive content that is received from the given OEM component.

System(s) and method(s) for enforcing consistency of value(s) and unit(s) in a vehicular environment

Implementations described herein relate to determining how to fulfill a spoken utterance based on a user that provided the spoken utterance. For example, implementations can receive a spoken utterance from a user, determine a set of fulfillment actions for the spoken utterance, and determine whether the user that provided the spoken utterance corresponds to a first user or a second user. Further, and in response to determining that the user corresponds to the first user, implementations can select a subset of first fulfillment action(s) from the set, and cause the subset of first fulfillment action(s) to be implemented to satisfy the spoken utterance. Moreover, and in response to determining that the user corresponds to the second user, implementations can select a subset of distinct, second fulfillment action(s) from the set, and cause the subset of second fulfillment action(s) to be implemented to satisfy the spoken utterance.

Dynamically adapting fulfillment of a given spoken utterance based on a user that provided the given spoken utterance

Implementations described herein relate to various techniques for biasing interpretations of spoken utterances that are received in a vehicular environment. For example, implementations can receive a spoken utterance that includes a query from a user of a vehicle and obtain a corresponding vehicle sensor data instance generated by vehicle sensor(s) of the vehicle. Some implementations can determine to execute a search over only a first corpus of data, but not a second corpus of data, to obtain a given response to the query based on various criteria, including at least the query, the corresponding vehicle sensor data instance, a corresponding timestamp associated with the corresponding vehicle sensor data instance, and/or a corresponding duration of time the user has been associated with the vehicle. Additional, or alternative, implementations can execute a search over both the first and second corpora of data, and obtain the given response based on the criteria.

Biasing interpretations of spoken utterance(s) that are received in a vehicular environment

Methods and systems for efficient query rewriting and the like are described here. One such described method comprises: offline mapping frequently-seen search queries to rewritten queries that may be better for searching; offline caching the mapping in a cache memory; and upon receiving a search query from a user similar to one of the mapped search queries, obtaining a corresponding rewritten query from the mapping in the cache memory based on predetermined conditions, and issuing a search of the rewritten query to the backend data system in order to avoid having to issue a search query to the backend data system twice while the user is online.

Methods and systems for efficient query rewriting

A stopword detection component detects stopwords (also stop-phrases) in search queries input to keyword-based information retrieval systems. Potential stopwords are initially identified by comparing the terms in the search query to a list of known stopwords. Context data is then retrieved based on the search query and the identified stopwords. In one implementation, the context data includes documents retrieved from a document index. In another implementation, the context data includes categories relevant to the search query. Sets of retrieved context data are compared to one another to determine if they are substantially similar. If the sets of context data are substantially similar, this fact may be used to infer that the removal of the potential stopword(s) is not material to the search. If the sets of context data are not substantially similar, the potential stopword can be considered material to the search and should not be removed from the query.

Locating meaningful stopwords or stop-phrases in keyword-based retrieval systems

Efficient query rewriting

Methods, systems, and computer program products are provided for interleaving search results. A method includes presenting multiple first search results received from a first search engine. The first search results satisfy a search query directed to the first search engine and are presented in an order. A second search result from a second search engine is inserted at a position between two otherwise adjacent first search results. The second search result is received from a second search engine in response to the search query.

Interleaving search results

A ranking component ranks documents, such as web pages or web sites, to obtain a ranking score that defines a quality judgment of the document. The ranking score of a particular document is based on the ranking score of the documents which link to it and based on affiliation among the documents.

Determining quality of linked documents

A system includes a ranking component that ranks nodes, such as web sites, to obtain ranking values that define a quality judgment of the nodes. The ranking values are based on links between the nodes and, among other things, deemphasize links between affiliated nodes. Additionally, the amount of rank that any particular node can contribute to another node may be capped at a threshold level, thus tending to prevent some nodes from unduly influencing the ranking values.

Ranking nodes in a linked database based on node independence

A system receives location identifiers associated with documents visited by one or more users. The system retrieves the documents using the received location identifiers and maps the retrieved documents to one or more topics. The system determines a popularity value associated with the retrieved documents and correlates the popularity value with the one or more topics to determine a per-topic popularity for the retrieved documents.

Systems and methods for correlating document topicality and popularity

Growing community of inventors

Palo Alto, CA, United States of America

Amit Singhal