Google Inc.

Uber Technologies, Inc.

Benjamin Ross

David Kliger Elson

David Eisenberg

Raj Agarwal

Kevin Jose Chavez

Sudeep Gandhe

Christa Wimberley

Ting Chen

Yu Luo

Kirk Rodrigues

Ujwala Prabhakar Tulshigiri

Yupeng Fu

Christopher Peck

Maksym Ivanchenko

Kaibo Wang

Yun Zhang

Systems and methods for compressing and querying data for real-time analytics. The system can receive log data and generate an intermediate representation by parsing a log template and variables from the log data into a columnar format. The method includes generating a compressed intermediate representation associated with an index type and storing the compressed intermediate representation in the columnar format based on the index type. The method includes receiving a search query and analyzing the search query to identify a user defined function. The method includes parsing the search query to convert the search query into one or more predicates that satisfy the search query. The method includes filtering the compressed log data based on the one or more predicates and providing a query result.

Data compression for real-time analytics

Systems and methods provides for dialog management in real-time rather than turn taking. An example method included generating first candidate responses to triggering event. The triggering event may be receipt of a live stream chunk for the dialog or receipt of a backend response to a previous backend request for a dialog shema. The method also includes updating a list of candidate responses that are accepted or pending with at least on of the first candidate responses, and determining, for the triggering event, whether the list of candidate responses includes a candidate response that has a confidence score that meets a triggering threshold. The method also includes waiting for a next triggering event without providing a candidate response when the list does not include a candidate response that has a confidence score that meets the triggering threshold.

Streaming real-time dialog management

Systems and methods provides for dialog management in real-time rather than turn taking. An example method included generating first candidate responses to triggering event. The triggering event may be receipt of a live stream chunk for the dialog or receipt of a backend response to a previous backend request for a dialog schema. The method also includes updating a list of candidate responses that are accepted or pending with at least on of the first candidate responses, and determining, for the triggering event, whether the list of candidate responses includes a candidate response that has a confidence score that meets a triggering threshold. The method also includes waiting for a next triggering event without providing a candidate response when the list does not include a candidate response that has a confidence score that meets the triggering threshold.

Systems and methods for annotating conversations between a user and an electronic assistant in a hierarchical manner are disclosed. An example system includes a data store of hierarchical annotation records. The hierarchical annotation records include root records and non-root records. Each root record has a conversation identifier and an annotation identifier. Each non-root record includes an annotation identifier and a parent identifier, the parent identifier being an annotation identifier of another record. At least some of the non-root records further include an annotation tag. The system generates a first new root record and first non-root records for an input dialog act and generates a second new root record and second non-root records for an output dialog act that is responsive to the input dialog act. At least one of the second non-root records includes an annotation tag linking back to a record of the first non-root records.

Hierarchical annotation of dialog acts

Systems and methods provide for dialog management in real-time rather than turn taking. An example method includes generating first candidate responses to a triggering event. The triggering event may be receipt of a live-stream chunk for the dialog or receipt of a backend response to a previous backend request for a dialog schema. The method also includes updating a list of candidate responses that are accepted or pending with at least one of the first candidate responses, and determining, for the triggering event, whether the list of candidate responses includes a candidate response that has a confidence score that meets a triggering threshold. The method also includes waiting for a next triggering event without providing a candidate response when the list does not include a candidate response that has a confidence score that meets the triggering threshold.

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New York, NY, United States of America

Benjamin Ross