Adobe, Inc.

Sanket Vaibhav Mehta

Balaji Vasan Srinivasan

Sopan Khosla

Tanya Goyal

Vishwa Vinay

Gaurav Verma

Ankur Jain

Sahith Thallapally

William Brandon George

Fan Du

Ritwik Sinha

Gaurush Hiranandani

Natwar Modani

John Bevil Bates

Subrata Mitra

Sunav Choudhary

Harsh Jhamtani

Cedric Huesler

Payal Bajaj

Shriram Venkatesh Shet Revankar

Said Kobeissi

Ivan Andrus

Chris Challis

Prithvi Bhutani

Mekala Rajasekhar Reddy

Aashaka Dhaval Shah

Harvineet Singh

Determination of high value customer journey sequences is performed by determining customer interactions that are most frequent as length N=1 sub-sequences, recursively determining most frequent length N+1 sub-sequences that start with the length N sub-sequences, determining a first count indicating how often one of the sub-sequences appears in the sequences, determining a second count indicating how often the one sub-sequence resulted in the goal, and using the counts to determine the most or least effective sub-sequences for achieving the goal.

Intelligent customer journey mining and mapping

Embodiments of the present invention provide systems, methods, and computer storage media directed to facilitate identification of security policies for documents. In one embodiment, content features are identified from a set of documents having assigned security policies. The content features and corresponding security policies are analyzed to generate a security policy prediction model. Such a security policy prediction model can then be used to identify a security policy relevant to a document.

Tagging documents with security policies

Embodiments relate to tenant-side detection and mitigation of performance degradation resulting from interference generated by a noisy neighbor in a distributed computing environment. A first machine-learning model such as a k-means nearest neighbor classifier is operated by a tenant to detect an anomaly with a computer system emulator resulting from a co-located noisy neighbor. A second machine-learning model such as a multi-class classifier is operated by the tenant to identify a contended resource associated with the anomaly. A corresponding trigger signal is generated and provided to trigger various mitigation responses, including an application/framework-specific mitigation strategy (e.g., triggered approximations in application/framework performance, best-efforts paths, run-time changes, etc.), load-balancing, scaling out, updates to a scheduler to avoid impacted nodes, and the like. In this manner, a tenant can detect, classify, and mitigate performance degradation resulting from a noisy neighbor.

Tenant-side detection, classification, and mitigation of noisy-neighbor-induced performance degradation

Techniques and systems are described in which a document management system is configured to update content of digital documents through use of static and transient tags. A transient tag, for instance, may be associated with portions of the digital document that may be changed and a static tag with portions of the digital document that are not to be changed. An update to the digital document is then triggered by a document management system based on a triggering change made to an initial document portion of the digital document having a transient tag, and is not based on changes made to portions having a static tag or are untagged.

Digital document update using static and transient tags

Techniques and systems are described in which a document management system is configured to update content of document portions of digital documents. In one example, an update to the digital document is initially triggered by a document management system by detecting a triggering change applied to an initial portion of the digital document. The document management system, in response to the triggering change, then determines whether trailing changes are to be made to other document portions, such as to other document portions in the same digital document or another digital document. To do so, triggering and trailing change representations are generated and compared to determine similarity of candidate document portions with an initial document portion.

Digital document update

A method for propagating changes from master content to variant content includes receiving, from a user interface, a modified master text composition that incorporates changes to a master text composition. Each of the master text composition, the modified master text composition, and a variant text composition assigned to the master text composition are divided into text units. A correspondence model is constructed that includes mappings between the text units of the master text composition, the text units of the modified master text composition, and the text units of the variant text composition. Proposed changes to the variant text composition are determined that correspond to the changes to the master text composition based on the mappings. At least one of the proposed changes is integrated into the variant text composition.

Propagation of changes in master content to variant content

The present disclosure is directed toward systems and method for generating geo-fences having boundaries around geographic regions of interest based on historical activity data of a user application on a plurality of client devices. For example, systems and methods described herein involve tracking activity data to identify instances of an application activity associated with an action to promote and identify locations where users more frequently perform the application activity. In addition, systems and methods described herein involve tracking activity data over time to determine geographic regions of interest at different time periods where users more frequently perform application activities. Further, systems and methods described herein involve generating geo-fences around one or more geographic regions of interest.

Generating data-driven geo-fences

Growing community of inventors

Pune, India

Sanket Vaibhav Mehta