Microsoft Technology Licensing, LLC

Linkedin Corporation

Yahoo! Inc.

Sanjay Kshetramade

Sanjay Sureshchandra Dubey

Ashvin Kannan

Nihar Niranjan Mehta

Carleton Miyamoto

Craig Martell

Aviad Pinkovezky

Muhieddine El Kaissi

Majid Yazdani

Alexander Chiocchi

Xiao Bao

Meera Gill Bhatia

Guangyu Dong

Eldo K Cherian

Kevin Mikles

Vikram Rangnekar

Douglas James Myers

Sophia H Nguyen

Brian Rumao

Kancheng Cao

Rajen Subba

A method is provided. The method comprises receiving, from a user device, a current search query that is in an unstructured format; after receiving the current search query from the user device, retrieving a corresponding current list of facets with a current list of associated values and a context of the current search query, the context comprising a previous search query from the user device and a corresponding previous list of facets with a previous list of associated values; determining a group of actions on one or more of the current list of facets with the current list of associated values and the previous list of facets with the previous list of associated values based on the current search query; creating an updated list of facets with an updated list of associated values based on the group of actions; generating a database query based on the updated list of facets with the updated list of associated values; causing a database search with the database query; transmitting a search result of the database search to the user device, wherein the method is performed by one or more computing devices.

Facet-based conversational search

A method is provided. The method comprises receiving a search query that is part of a search conversation, the search query in an unstructured format; identifying a first list of facets with a first list of associated values from the search query; deriving a second list of facets with a second list of associated values from the first list of facets based on a context of the search query within the search conversation; generating a database query based on the second list of facets with the second list of associated values; causing a database search with the database query; transmitting a search result of the database search to a sender of the search query, wherein the method is performed by one or more computing devices.

Methods, systems, and computer programs are presented for analyzing profiles and building profile models that can be used to personalize search results for a member on a social network. In example embodiments, a system aggregates data about members on the social network including member profile data, customer relation data, and member communication data. The system further extracts attribute values from the aggregated data and maps the attribute values onto attribute vectors on a social data map. Based on the mapping, the system determines a model member profile for the member. The system further generates candidate attribute vectors for search results from a search for the member and determines a similarity score between the model member profile and each candidate attribute vector. The system further ranks the search results based on the similarity score and presents a ranked display of the search results to the user.

Personalizing search and/or recommendation results based on member activity models

A system may include a database configured with individual partitions, one of the partitions corresponding to a sponsored content campaign of a social network. The system may further include multiple servers each communicatively coupled to the database, and each configured to implement a campaign having a campaign termination criterion. Each of the servers may include a processor configured to track sponsored content event data received from a user device based on the campaign and transmit the event data to the database and terminate the campaign based on a comparison of the event data as received from a partition of the database corresponding to the campaign and an estimation of event data not received from the database. The database may be configured to store the event data as received from the servers in the partition corresponding to the campaign upon receipt of the event data.

Independent targeted sponsored content management system and method

An autofill system is described for auto-populating electronic forms with data stored by an on-line social networking system. When a member of an on-line social network system accesses, via a web browser, an autofill-enabled web page, the autofill system determines an identification of the member, scrapes the member's profile to obtain member's information, assembles the member's profile information as member data, and communicates the member data to the web browser together with a script for presenting an autofill button on the web page.

Method and system for auto-populating electronic forms

A user may activate an embedded advertisement in an embedded window in a document, such as a web page. This embedded advertisement may be associated with a domain (a granddaughter domain) that is different than the domain associated with the embedded window (a daughter domain) and the domain associated with the document (a parent domain). In older browsers, cross-domain communication may not be supported in this circumstance. This problem is solved by opening a series of windows from the granddaughter domain, each of which is associated with a candidate origin of the document. Then, access commands associated with the windows are communicated to the domain of the document. Only the access command for the window having the correct origin of the domain of the document is processed, which results in content associated with the embedded advertisement being linked at a source and presented or displayed in the embedded advertisement.

Embedded-advertising content presented in document context

Methods, systems, and computer programs for triggering interaction with a Dynamic Online Community (DOC) are presented. In one embodiment, a method includes an operation for monitoring online activity of a user, which includes tracking user input on a web browser. The method further includes operations for detecting that the user is interested in a subject based on the online activity, and for determining whether there is a DOC topic that is associated with the subject. The DOC has members that have shown an interest in the DOC topic. In another operation, the method assigns the user to be a member of the DOC if the determination indicates that there is a DOC topic associated with the subject. The user is automatically recommended to join the DOC. DOC related information is provided to the user after the user is assigned to the DOC. In one embodiment, the online activity of the user is searching in a search provider's website.

Dynamic online communities

Growing community of inventors

Fremont, CA, United States of America

Sanjay Kshetramade