Abstract: In an example embodiment, two machine learned models are trained. One is trained to output a probability that a searcher having a member profile in a social networking service will select a potential search result. The other is trained to output a probability that a member corresponding to a potential search result will respond to a communication from a searcher. Features may be extracted from a query, information about the searcher, and information about the member corresponding to the potential search result and fed to the machine learned models. The outputs of the machine learned models can be combined and used to rank search results for returning to the searcher.

Abstract: Techniques for improving search using generalized linear mixed models are disclosed herein. In some embodiments, a computer-implemented method comprises: receiving a search query comprising at least one search term and being associated with a user; extracting features from corresponding profiles of a plurality of candidates; for each one of the candidates, generating a corresponding score based on a generalized linear mixed model comprising a generalized linear query-based model and a random effects user-based model; selecting a subset of candidates from the plurality of candidates based on the corresponding scores; and causing the selected subset of candidates to be displayed to the user in a search results page for the search query.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method described herein are directed to a Similar Profiles Engine. The Similar Profiles Engine generates an inverted index query based on one or more portions of profile data of a target member account of a social network service. The Similar Profiles Engine identifies respective profile data, of one or more candidate member accounts in the social network service, that maps to at least one inverted index filter, the at least one inverted index filter matching at least a portion of the inverted index query. The Similar Profiles Engine calculates a similarity score between each respective candidate member account and the target member account, and causes a display of identifiers of one or more candidate member accounts in a user interface of a client device based on respective similarity scores.

Abstract: Images can be used to determine the size of an article of clothing matching the physical characteristics of a user. An image can include an article of clothing known to fit well or a representation of a body part, which can comprise the body part itself. Images can also include a reference item. Various techniques are used to determine one or more perspective distortions in the image based on analysis of the reference item and information known about the reference item. The one or more perspective distortions can be accounted for to determine physical characteristics of the article of clothing or the body part associated with the article of clothing. The physical characteristics can be used to determine the size of an article of clothing matching, or corresponding to, the physical characteristics.

Abstract: A machine is configured to improve a search engine. For example, the machine generating, for a user, one or more search facets using one or more machine learning algorithms. The generating of the search facets is based on a user profile associated with the user and one or more similar user profiles. The machine receives an identifier of the user from a client device. The machine causes a display of one or more selectable identifiers of the one or more search facets in a user interface of the client device associated with the user. The machine receives, from the client device, an indication of a selection of the one or more selectable identifiers of the one or more search facets. The machine causes a display of one or more job descriptions in the user interface based on a search performed using the one or more search facets.

Abstract: A system and method includes receiving a search query and obtaining, from a database, member data of a member. For each of a plurality of nonlinear models, the nonlinear model is traversed based on a comparison of characteristics to conditions to obtain a score, wherein, among the nonlinear models, at least one characteristic is an inferred characteristic based on at least one of: activities by the member in an online networking system; and connections by the member in the online networking system. The score obtained from each of the nonlinear models is combined to obtain a combined score and a user interface to displays information related to the member based, at least in part on the combined score.

Abstract: A system and method includes receiving a search query and obtaining, from a database, member data of a member. For each of a plurality of nonlinear models, the nonlinear model is traversed based on a comparison of characteristics to conditions to obtain a score, wherein, among the nonlinear models, at least one characteristic is an inferred characteristic based on at least one of: activities by the member in an online networking system; and connections by the member in the online networking system. The score obtained from each of the nonlinear models is combined to obtain a combined score and a user interface to displays information related to the member based, at least in part on the combined score.

Abstract: Techniques for improving search using generalized linear mixed models are disclosed herein. In some embodiments, a computer-implemented method comprises: receiving a search query comprising at least one search term and being associated with a user; extracting features from corresponding profiles of a plurality of candidates; for each one of the candidates, generating a corresponding score based on a generalized linear mixed model comprising a generalized linear query-based model and a random effects user-based model; selecting a subset of candidates from the plurality of candidates based on the corresponding scores; and causing the selected subset of candidates to be displayed to the user in a search results page for the search query.

Abstract: In an example embodiment, two machine learned models are trained. One is trained to output a probability that a searcher having a member profile in a social networking service will select a potential search result. The other is trained to output a probability that a member corresponding to a potential search result will respond to a communication from a searcher. Features may be extracted from a query, information about the searcher, and information about the member corresponding to the potential search result and fed to the machine learned models. The outputs of the machine learned models can be combined and used to rank search results for returning to the searcher.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method described herein are directed to a Similar Profiles Engine. The Similar Profiles Engine generates an inverted index query based on one or more portions of profile data of a target member account of a social network service. The Similar Profiles Engine identifies respective profile data, of one or more candidate member accounts in the social network service, that maps to at least one inverted index filter, the at least one inverted index filter matching at least a portion of the inverted index query. The Similar Profiles Engine calculates a similarity score between each respective candidate member account and the target member account, and causes a display of identifiers of one or more candidate member accounts in a user interface of a client device based on respective similarity scores.

Abstract: Disclosed in some examples are methods, systems, and machine readable mediums which provide for retrieval, ranking, and display of candidates that are more likely to respond to employment inquiries in an employment search graphical user interface (GUI). The system may employ a machine learning algorithm which may calculate a score for each member of the social networking service that predicts, based upon one or more features how likely the individual is to respond to a message. In some examples, the candidates that are determined to be more likely to respond may be presented as a selectable option in the GUI.

Abstract: Disclosed in some examples are methods, systems, and machine readable mediums which provide for retrieval, ranking, and display of candidates that are more likely to respond to employment inquiries in an employment search graphical user interface (GUI). The system may employ a machine learning algorithm which may calculate a score for each member of the social networking service that predicts, based upon one or more features how likely the individual is to respond to a message. In some examples, the candidates that are determined to be more likely to respond may be presented as a selectable option in the GUI.

Abstract: Techniques to determine the three-dimensional structure of wearable items are disclosed. A scanning device can project waves at a wearable item and receive reflections of the waves. In embodiments, the scanning device projects light pulses and detects reflections of the light pulses. Depth measurements from the scanning device to the wearable item can be used to determine points corresponding to locations on the wearable item. A point cloud can be generated of the points, which can convey the three-dimensional structure of the wearable item. In embodiments, another wearable item can be determined to have a corresponding three-dimensional structure based on point cloud comparisons. The second wearable item can be suggested to a user as a wearable item having an appropriate fit for the user.