Microsoft Technology Licensing, LLC

David Benjamin Liu

Lei Zhang

Hao Liu

Tianjing Xu

Shanshan Liu

Ao Guo

Jian Zhou

Miao Zou

Yucao Wang

Danmeng Liu

Gang Hua

Paul A Viola

Akhilesh Gupta

Ajith Muralidharan

Guanchao Wang

Sandor Nyako

Swapnil Ghike

Swetha Nagabhushan Karthik

Changji Shi

Gargi Harish Bhandari

Rakesh Malladi

Ruiqi Wang

Netra Malagi

Amit Ruparel

Cheng-Fu Lin

The present disclosure provides technical solutions related to intelligent cloud management based on profile. Artificial intelligent is applied to cloud management and cloud management suggestion may be proposed intelligently. In daily work, behaviors in using cloud resources may show characteristics of cloud users or cloud tenants themselves. The technical solution of intelligent cloud management of the present disclosure generates profile identifying cloud using characteristics by extracting behavior data in using cloud and intelligently proposes cloud management suggestions based on the profile.

Intelligent cloud management based on profile

Technologies for unseen notification handling are described. Embodiments select an initial set of notifications, provide the selected initial set of notifications to a client device, store seen notifications in a first data store, maintain sent but unseen notifications in a second data store that is an in-memory online data store, retrieve a set of the sent but unseen notifications from the second data store, create a list of unseen notifications by combining the retrieved set of sent but unseen notifications with a set of unsent and unseen notifications, generate a set of relevance scores for the list of unseen notifications, create a new version of the list of unseen notifications based on the new set of relevance scores, and provide the new version of the list of the unseen notifications to the client device.

Read-time relevance-based unseen notification handling

Intelligent assistant for cloud management

Techniques for broadcasting notifications with low latency are provided. A set of recipients for a notification of a content item is determined. The notification is stored in a second notifications storage that is separate from a first notifications storage. A request for one or more notifications is received over a computer network from a client device that is associated with a particular recipient in the set of recipients. In response to receiving the request, first notification data is retrieved from the first notifications storage, second notification data that includes the notification is retrieved from the second notifications storage. The first notification data is combined with the second notification data to generate combined notification data. The combined notification data is transmitted over the computer network to the client device and is stored in the first notifications storage. The notification may be removed from the first notifications storage.

Broadcasting notifications with low latency

Image feature selection and extraction (e.g., for image classifier training) is accomplished in an integrated manner, such that higher-order features are merely developed from first-order features selected for image classification. That is, first-order image features are selected for image classification from an image feature pool, initially populated with pre-extracted first-order image features. The selected first-order classifying features are paired with previously selected first-order classifying features to generate higher-order features. The higher-order features are placed into the image feature pool as they are developed or 'on-the-fly' (e.g., for use in image classifier training).

Feature selection and extraction

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Santa Clara, CA, United States of America

David Benjamin Liu