Microsoft Technology Licensing, LLC

Alexander Easton

Sanjay Sachdev

Sean S Peng

Venkata S J R Bhamidipati

A method and apparatus for a self-learning user interface is provided. The method comprises receiving selection data that indicates a first plurality of user selections with respect to a first plurality of views of a workflow associated with a task; receiving an instruction to initiate a current session of the workflow; accessing the selection data and one or more models of user behavior generated from a second plurality of user selections associated with a plurality of users; determining a plurality of elements that were not selected by the user; determining to remove at least one of the first plurality of views of the workflow or a subset of the plurality of elements; generating a second plurality of views of web content for the user by excluding the removed at least one of the first plurality of views of the workflow or the removed subset of the plurality of elements.

Self-learning user interface

Techniques for monitoring performance of a computer system are provided. Bucket data is stored that indicates that multiple buckets are associated with a particular type of request. Then, multiple requests are received, where a first request and a second request indicate the same type of request. Based on the bucket data, the first request is assigned to a first bucket and the second request is assigned to a second bucket. The assignment may be further based on a complexity determined for each request. First performance data is generated while processing the first request and is aggregated with second performance data that was generated while processing one or more third requests that are assigned to the first bucket. Third performance data is generated while processing the second request and aggregated with fourth performance data that was generated while processing one or more fourth requests that are assigned to the second bucket.

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San Jose, CA, United States of America

Alexander Easton