| Patent application number | Description | Published |
|---|
| 20140025673 | TECHNIQUES FOR ESTIMATING DISTANCE BETWEEN MEMBERS OF A SOCIAL NETWORK SERVICE - Techniques for estimating, in real time, the likelihood that any particular member of a social network service is a third degree connection of another member are described. Consistent with some embodiments, various member profile attributes of a member are used as a sort of proxy for determining the likelihood or probability that the member is a third degree connection of another member. For example, in some instances, the number of first-degree connections a member has is used to derive a probability score indicating the likelihood that the member is a third-degree connection of another member, such as a person performing a people-search. Once derived, the probability score for each member may be used in various applications, such as a people-search engine, to boost or increase a ranking score assigned to each search result and used to order the search results when presented to the user who has performed the search. | 01-23-2014 |
| 20140129552 | LEVERAGING HOMOPHILY IN RANKING SEARCH RESULTS - Techniques for ranking search results generated by a search engine are described. Consistent with some embodiments, a search engine processes a search query to identify member profiles of members of a social network service for presentation in a search results page or user interface. The member profiles are presented in the search results ordered based on a ranking score that is derived at least in part by identifying similarities in the member profile attributes of the member profiles satisfying the search query and the member profile of the person performing the search. Accordingly, to the extent that a member profile has similarities shared in common with the member profile of the member performing the search, that member profile is more likely to be presented more prominently in the search results. | 05-08-2014 |
| 20140214815 | DISPLAYING RESULTS OF QUERIES FOR INFORMATION WITHIN SOCIAL NETWORKS - Systems and methods for searching for information within social networks are described. In some examples embodiments, a search assist system receives a query, such as a partial query, identifies two or more categories of data that include information satisfying the query, ranks the identified categories of data based on various selection criteria, and presents suggested search terms based on the rankings. | 07-31-2014 |
| 20140214822 | SEARCHING FOR INFORMATION WITHIN SOCIAL NETWORKS - Systems and methods for searching for information within social networks are described. In some examples embodiments, a search assist system receives a query, such as a partial query, identifies two or more categories of data that include information satisfying the query, ranks the identified categories of data based on various selection criteria, and presents suggested search terms based on the rankings. | 07-31-2014 |
| 20150317314 | CONTENT SEARCH VERTICAL - Disclosed in some examples are methods, systems, and machine readable mediums which find a special set of keywords which, when used to search a supplemental set of search verticals (e.g., the newly added search verticals), return high quality results. When a user enters a search containing one or more keywords from the special set of keywords, the system may search both the standard set of search verticals (as normal), but also the one or more keywords may be used to search the supplemental set of search verticals. Results from both may then be presented to the user. | 11-05-2015 |
| 20150347414 | NEW HEURISTIC FOR OPTIMIZING NON-CONVEX FUNCTION FOR LEARNING TO RANK - Techniques for optimizing non-convex function for learning to rank are described. Consistent with some embodiments, a search module may set an order for a group of search features. The group of search features can be used by a ranking model to determine the relevance of items in a search query. Additionally, the search module can assign a first weight factor to a first search feature in the group of search features. Moreover, the search module can calculate a mean reciprocal rank for the search query based on the assigned first weight factor. Furthermore, the search module can determine a second weight factor, using a preset incremental vector, for a second search feature in the group of search features to maximize the mean reciprocal rank for the search query. Subsequently, the search module can assign the second weight factor to the second search feature in the group of search features. | 12-03-2015 |
| 20150347974 | MULTI-OBJECTIVE RECRUITER SEARCH - A system includes a database, a network interface, and a processor. The database includes, for each multiple users of a social network, profile data and activities, by the user, related to the social network. The network interface is configured to be communicatively coupled to user devices associated with the population of users. The processor is configured to obtain a recruitment search query for a position in an organization, compare the recruitment search query against the profile data of at least some of the users to obtain a comparison, determine, for each of the at least some of the users, a likelihood of interacting with a recruiter associated with the position based on the activities of each of the at least some of the users, and transmit, to at least one of the users, a communication related to the position based, at least in part, on the comparison and the likelihood of interacting. | 12-03-2015 |
| 20160034464 | PERSONALIZED SEARCH BASED ON SEARCHER INTEREST - A system and method for personalized search based on searcher interest may include obtaining a search term from a member of a social network at a user device via the network interface. An initial result may be generated based on the search term, including a first group of content items from a social network and stored in a content database, the content items including member profiles of members of the social network. Each of the content items of the first group may be ranked based on information from an activity database, the activity database storing the information related to the social network, the activities including interactions with search results that include ones of the member profiles. A second group of the content items may be displayed, including at least some of the first group of the content items, based on the rank of the first group of the content items. | 02-04-2016 |
| 20160034465 | PERSONALIZED SEARCH BASED ON SIMILARITY - A system and method for personalized search based on similarity may include obtaining a search term. An initial result based on the search term and including a first group of content items as stored in a content database may be generated. Each of the content items of the first group may be ranked based, at least in part, on similarity scores, each of the similarity scores individually based on a first member profile relative to individual ones of second member profiles to which an activity related to a content item of the first group corresponds. The user device may display a second group of the content items, including at least some of the first group of the content items, according to the rank of the first group of the content items. | 02-04-2016 |
| 20160034466 | PERSONALIZED SEARCH USING SEARCHER FEATURES - A system and method for personalized search user searcher features may include obtaining a search term from a member of a social network at a user device via the network interface. An initial result may be generated based on the search term, including a first group of content items from a social network and stored in a content database, the content items including member profiles of members of the social network. Each of the content items of the first group may be ranked based on information indicative of interactions from an activity database with the content items of the first group, the interactions being by at least a second user of the social network different than the first user. A second group of the content items may be displayed, including at least some of the first group of the content items, based on the rank of the first group of the content items. | 02-04-2016 |
