Abstract: Implementations described herein are directed to enabling collaborative ranking of interpretations of spoken utterances based on data that is available to an automated assistant and third-party agent(s), respectively. The automated assistant can determine first-party interpretation(s) of a spoken utterance provided by a user, and can cause the third-party agent(s) to determine third-party interpretation(s) of the spoken utterance provided by the user. In some implementations, the automated assistant can select a given interpretation, from the first-party interpretation(s) and the third-party interpretation(s), of the spoken utterance, and can cause a given third-party agent to satisfy the spoken utterance based on the given interpretation.

Abstract: Implementations described herein are directed to enabling collaborative ranking of interpretations of spoken utterances based on data that is available to an automated assistant and third-party agent(s), respectively. The automated assistant can determine first-party interpretation(s) of a spoken utterance provided by a user, and can cause the third-party agent(s) to determine third-party interpretation(s) of the spoken utterance provided by the user. In some implementations, the automated assistant can select a given interpretation, from the first-party interpretation(s) and the third-party interpretation(s), of the spoken utterance, and can cause a given third-party agent to satisfy the spoken utterance based on the given interpretation.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium including receiving user interaction data, wherein the user interaction specifies user interactions with content items and conversion items. A conversion item is a user action that satisfies a predetermined conversion criteria. The method includes receiving conversion data including conversion path data for a plurality of conversion paths, wherein each conversion path includes user interaction data prior to and including a conversion event. The method includes determining a first interaction, an assist interaction or a last interaction with content items for the conversion event. The method includes providing an ability to define a segment, using a processor, the conversion path data based on path-level dimensions and path-level metrics.

Abstract: Distributed metrics collection systems and methods can be used to help bind together a large organization by implementing both formal and informal information flows. Hierarchical reporting and tasking are formal information flows. Gossip is an informal information flow. Users use a set of modules to configure distributed metrics collection. Management type users can configure data flows that appear similar to hierarchical reporting. All users can configure data flows that simply distribute items of interest. Over time, the data flows evolve in an organic manner as users appear, move, change interests, and leave.

Abstract: Distributed metrics collection systems and methods can be used to help bind together a large organization by implementing both formal and informal information flows. Hierarchical reporting and tasking are formal information flows. Gossip is an informal information flow. Users use a set of modules to configure distributed metrics collection. Management type users can configure data flows that appear similar to hierarchical reporting. All users can configure data flows that simply distribute items of interest. Over time, the data flows evolve in an organic manner as users appear, move, change interests, and leave.