Microsoft Technology Licensing, LLC

Vmware, Inc.

Linkedin Corporation

Rahul Agarwal

Senthil Sundaram

Etienne Robert Le Sueur

Sunny Tulsi Sreedhar Murthy

Gal Yardeni

Sandhya Pai

Steven Taylor

Sindhu Shashidhara

Alexandre Lee

Seema Lal Gulabrani

Ajay Vellanki

Arun Mudiraj

Praveen Sinha

Disclosed are various embodiments for creating and managing virtual appliances. A command to create a virtual machine image for a hosted instance of an application image is received. The virtual machine image is created in response to receiving the command. The virtual machine image can include an operating system; a container orchestration service configured to host the instance of the application image; and a configuration service. The configuration service can be configured to at least install a management agent in response to a first boot of the virtual machine and configure the management agent to download and install the application image.

Managed virtual appliances

A system is described for automatically calibrating a display device based at least on information relating to a user of the display device. The system obtains visual acuity information or pupillary information of the user. The system then determines a value of a display parameter of the display device based at least on the visual acuity information or the pupillary information of the user. The determined value is then provided for application to the display device. Other information may also be used in determining the value of the display parameter, such as user input, demographic information of the user, display device specific information, user environment information, displayed content information, or application context information. An algorithm may be used that determines the display parameter based on such information. The algorithm may comprise a model obtained through machine learning.

Self-calibrating display device

Techniques for ranking search results generated by a search engine are described. A search query initiated by a searcher is processed to identify a set of member profiles satisfying the search query. A ranking score is assigned to each member profile of the set of member profiles. A subset of the set of member profiles is identified based on a determination of an overlap between a work history specified in each of the subset of member profiles and a work history specified in a profile of the searcher. The ranking score assigned to a member profile of the subset of the set of member profiles is adjusted based on the determination. A portion of each of the set of member profiles satisfying the search query is communicated for presentation as search results in a search results interface.

Adjusting search results based on overlapping work histories

Systems and methods for ranking search results based on members' posting activity and content are disclosed. The social networking system receives a search request for at least one member profile and retrieves member profiles in response to the search request. For a member profile in the member profiles, the social networking system identifies at least one submitted content item associated with the member profile and analyzes the at least one submitted content item to determine topics associated with the at least one submitted content item. The social networking system generates a topic similarity score for the member profile based on a comparison of the topics and a topic of interest associated with the search request. The social networking system ranks the member profiles based on generated topic similarity scores. The social networking system selects at least one member profile based on the member profile ranking.

Ranking search results based on members? posting activity and content

Techniques for improving rankings of search results generated by a search engine are described. A set of member profiles is identified. The identifying is based on keywords specified in a search query matching search index entries corresponding to the set of member profiles. A subset of the member profiles is selected. The selecting is based on a matching of the keywords to special index entries associated with the subset of the member profiles. The special index entries represent values of data fields specified in each of the subset of the set of member profiles. The special index entries also represent relationships between the values of the data fields. Ranking scores associated with each of the subset of the member profiles are boosted. A portion of each of the set of member profiles is communicated for presentation in user interface in order of the ranking scores.

Enhancing rankings of search results for member profile queries

Techniques for enhancing search results generated by a search engine are described. A first set of member profiles is identified, the first set of member profiles satisfying a search query initiated by a searcher. A second set of member profiles is identified, the second set of member profiles having a relationship between a profile of the searcher and each of the second set of member profiles. A subset of the second set of member profiles is selected based on strength of relationships between each of the subset of the second set of member profiles and the first set of member profiles. A portion of each of the first set of member profiles is communicated for presentation in a first region of a search results user interface and a portion of each of the subset of the second set of member profiles is communicated for presentation in a second region of the search results user interface.

Growing community of inventors

Sunnyvale, CA, United States of America

Rahul Agarwal