Methods, apparatus, systems, and computer-readable media are provided for providing context specific schema files that allow an automated assistant to broker human-to-computer dialogs between a user and an application that is separate from the automated assistant. The context specific schema file can provide the automated assistant with sufficient data to be responsive to user queries without necessarily communicating with a remote device, such as a server. Multiple different context specific schema files can be made available to the automated assistant according to a context in which a user is interacting with the automated assistant. In this way, latency otherwise exhibited by the automated assistant can be mitigated by providing the automated assistant with the information needed to respond to a user without continually retrieving the information over a network.

A processor may determine indexing information for indexing a document. The indexing information may comprise at least one index extracted from the document. The processor may identify at least one code page associated with the document. The processor may store the indexing information in association with code page information indicating the at least one code page. In response to a search query, the processor may determine a relevance degree between the document and the search query based on the indexing information and the code page information.

A processor may determine indexing information for indexing a document. The indexing information may comprise at least one index extracted from the document. The processor may identify at least one code page associated with the document. The processor may store the indexing information in association with code page information indicating the at least one code page. In response to a search query, the processor may determine a relevance degree between the document and the search query based on the indexing information and the code page information.

Methods and apparatuses for providing a real-time enterprise knowledge assistant that automatically responds to user comments and questions via a graphical user interface are described. The enterprise knowledge assistant may display automated responses to questions provided by users within a persistent chat channel (or other communications channel). The information displayed or referenced (e.g., via a linked electronic document) within an automated response to a user's factual question may be determined based on access rights to linked documents and the number of electronic interactions between users, such as the number of times that users co-edited or collaborated on documents (e.g., programming code). Upon detection that at least a portion of a user's message within a chat channel has been classified as a factual question, the enterprise knowledge assistant may access question and answer pairings stored within a frequently asked questions database and display an authorized answer.

Methods and apparatuses for providing a real-time enterprise knowledge assistant that automatically responds to user comments and questions via a graphical user interface are described. The enterprise knowledge assistant may display automated responses to questions provided by users within a persistent chat channel (or other communications channel). The information displayed or referenced (e.g., via a linked electronic document) within an automated response to a user's factual question may be determined based on access rights to linked documents and the number of electronic interactions between users, such as the number of times that users co-edited or collaborated on documents (e.g., programming code). Upon detection that at least a portion of a user's message within a chat channel has been classified as a factual question, the enterprise knowledge assistant may access question and answer pairings stored within a frequently asked questions database and display an authorized answer.

Methods and systems for structuring, storing and displaying time series data in a user interface. One system includes processors executing instructions to determine, from time series data from a first sensor, a first subset of time series data for the first batch from the first start time and the first end time, determine, from the time series data from the first sensor, a second subset of time series data for the second batch from the second start time and the second end time, generate a time series user interface comprising a chart, the chart including a first plot for the first subset of time series data and a second plot for the second subset of time series data, the first plot being aligned to the second plot, and cause presentation of the time series user interface.

Methods and systems for structuring, storing and displaying time series data in a user interface. One system includes processors executing instructions to determine, from time series data from a first sensor, a first subset of time series data for the first batch from the first start time and the first end time, determine, from the time series data from the first sensor, a second subset of time series data for the second batch from the second start time and the second end time, generate a time series user interface comprising a chart, the chart including a first plot for the first subset of time series data and a second plot for the second subset of time series data, the first plot being aligned to the second plot, and cause presentation of the time series user interface.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a predictive system that obtains and processes data describing terms for different medical concepts to generate commands from a user query. An entity module of the system determines whether a term describes a medical entity associated with a healthcare condition affecting an individual. When the term describes the medical entity an encoding module links the medical entity with a specified category based on an encoding scheme. The system receives the user query. A parsing engine of the system uses the received query to generate a machine-readable command by parsing the query against terms that describe the medical entity and based on the encoding scheme for linking the medical entity to the specified category. The system uses the command to query different databases to obtain data for generating a response to the received query.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a predictive system that obtains and processes data describing terms for different medical concepts to generate commands from a user query. An entity module of the system determines whether a term describes a medical entity associated with a healthcare condition affecting an individual. When the term describes the medical entity an encoding module links the medical entity with a specified category based on an encoding scheme. The system receives the user query. A parsing engine of the system uses the received query to generate a machine-readable command by parsing the query against terms that describe the medical entity and based on the encoding scheme for linking the medical entity to the specified category. The system uses the command to query different databases to obtain data for generating a response to the received query.

A transcription of audio speech included in electronic content associated with a meeting is created by an ASR model trained on speech-to-text data. The transcription is post-processed by modifying text included in the transcription, for example, by modifying punctuation, grammar, or formatting introduced by the ASR model and by changing or omitting one or more words that were included in both the audio speech and the transcription. After the transcription is post-processed, output based on the post-processed transcription is generated in the form of a meeting summary and/or template.