Adobe, Inc.

Adaptive Computing Enterprises, Inc.

Joshua Butikofer

Trevor Paulsen

Adrian Tanase

William Brandon George

Balaji Krishnamurthy

Nikaash Puri

Mihir Naware

Lauren Dest

Kumar Mrityunjay Singh

Hyman Chung

Yaman Kumar

Kunal Kumar Jain

Brandon Pack

Matthew William Rozen

Pranjal Prasoon

Somesh Singh

Suman Basetty

Clinton Hansen Goudie-Nice

James Patrick O'Reilly

Abhinav Chauhan

Mihai Corlan

Timothy Chia-chi Liu

Alexander Klimetschek

Ankita Mahajan

Douglas Reed Wightman

Alexandra Strawn

This disclosure involves using data science notebooks to customize and apply a visitor stitching framework. An event management system provides an initial visitor stitching framework via a data science notebook, wherein the data science notebook is an interactive environment for managing algorithms and data. The event management system receives, from a resource provider system via the data science notebook, a modification to the initial visitor stitching framework. The event management system applies the modification to the initial visitor stitching framework to generate a custom visitor stitching framework. The event management system processes a dataset associated with the resource provider system and a user using the custom visitor stitching framework to generate a stitched dataset associated with the user.

Visitor stitching with data science notebooks

This disclosure involves stitching event data using identity mappings. An event analytics system generates and stores an event dataset including first event data for a first set of events associated with a user. The first event data includes timestamps and a device identifier. The system identifies second event data for a second event associated with the user. The second event data includes a timestamp, the device identifier, and a user identifier. The system appends the second event data to the event dataset. Based on the second event data, the system generates and stores an identity mapping that maps the device identifier to the user identifier. Based on the identity mapping and a predetermined look-back window, the system updates the first event data to include the user identifier.

Stitching event data using identity mappings

Content creation techniques are described that leverage content analytics to provide insight and guidance as part of content creation. To do so, content features are extracted by a content analytics system from a plurality of content and used by the content analytics system as a basis to generate a content dataset. Event data is also collected by the content analytics system from an event data source. Event data describes user interaction with respective items of content, including subsequent activities in both online and physical environments. The event data is then used to generate an event dataset. An analytics user interface is then generated by the content analytics system using the content dataset and the event dataset and is usable to guide subsequent content creation and editing.

Content analytics as part of content creation

This disclosure involves stitching event data using identity mappings. An event analytics system generates and stores an event dataset including first event data for a first set of events associated with a user. The first event data includes timestamps and a device identifier. The system identifies second event data for a second event associated with the user. The second event data includes a timestamp, the device identifier, and a user identifier. The system appends the second event data to the event dataset. Based on the second event data, the system generates and stores an identity mapping that maps the device identifier to the user identifier. Asynchronously to generating and storing the event dataset, based on the identity mapping and a predetermined look-back window, the system updates the first event data to include the user identifier.

This disclosure involves performing event analytics on-the-fly based on user input to an analysis interface. An event analytics system correlates a plurality of event datasets to include a common visitor identifier. The system causes display, via the analysis interface, of information about the plurality of event datasets. The system receives, via the analysis interface, user selection of one or more event datasets, of the plurality of event datasets. Based on the selected one or more event datasets, the system generates a combined event dataset. The event analytics system receives, via the analysis interface, user input specifying information requested about the combined event dataset. The system obtains the requested information about the combined event dataset. The system causes display, via the analysis interface, of a visualization of the obtained information, wherein the visualization is based on event data from the combined event dataset in chronological order.

Real-time interactive event analytics

Disclosed herein are systems, methods, and non-transitory computer-readable storage media for constraining auto live migration of virtual machines using group tags, access control lists, and time constraints. A system assigns a hypervisor a group tag denoting membership in a group and assigns a virtual machine an affinity group tag that denotes a placement requirement on hypervisors. The affinity group tag can be positive, requiring a match, or negative, requiring a non-match. The system migrates the virtual machine to the hypervisor according to compatibility between the group tag and the affinity group tag. Limitations of virtual machine placement and live migration due to group tags can be overridden in the system by a forced migration triggered by a human or qualifying event. Additionally, an access control list can be added to group membership of hypervisors and a time dimension can be added to a group tag or an access control list.

System and method of constraining auto live migration of virtual machines using group tags

Growing community of inventors

Lehi, UT, United States of America

Joshua Butikofer