Patent application number | Description | Published |
20130031090 | METHODS AND SYSTEMS FOR IDENTIFYING SIMILAR PEOPLE VIA A BUSINESS NETWORKING SERVICE - Techniques for identifying and presenting member profiles similar to a source member profile are described. With some embodiments, a general recommendation engine is used to extract features from member profiles, and then store the extracted features, including any computed, derived or retrieved profile features, in an enhanced member profile. In real-time, the general recommendation engine processes client requests to identify member profiles similar to a source member profile by comparing select profile features stored in the enhanced member profile with corresponding profile features of the source member profile, where the comparison results in several similarity sub-scores that are then combined in accordance with directives set forth in a configuration file. Finally, the member profiles with the highest similarity scores corresponding with the user-selected member profile are selected, and in some instances, presented to a user. | 01-31-2013 |
20130318180 | LEVERAGING A SOCIAL GRAPH TO DELIVER RELEVANT RECOMMENDATIONS - Techniques for leveraging a social graph to identify senders and recipients of relevant recommendations and to facilitate the delivery of the relevant recommendations from the senders to the recipients are described. For example, a recommender is identified based on the recommender being a member of a social networking service who has interacted with an item of web-based content. A recommendee is identified based on the recommendee being another member of the social networking service who is connected to the recommender via a social graph maintained by the social networking service and based on having an affinity score for the item that exceeds a recommendee affinity score threshold and a connection strength to the recommender that exceeds a connection strength threshold. The recommender is sent a communication that invites the recommender to recommend the item to the recommendee. With some example embodiments, the communication is sent to the recommender within a pre-determined time measured from the time the recommender initiated an interaction with the item of web-based content. | 11-28-2013 |
20140136433 | REFERRING MEMBERS OF A SOCIAL NETWORK AS JOB CANDIDATES - Systems and methods for referring members of a social network as job candidates are described. In some examples, the systems and methods receive information associated with a job or a company associated with a job, identify members of a social network based on attributes for the members, and perform an action (e.g., send an email or update a widget on a profile page) associated with a member of the social network that is connected to the identified members and affiliated with the company. | 05-15-2014 |
20140136434 | REFERRING MEMBERS OF A SOCIAL NETWORK AS JOB CANDIDATES - Systems and methods for referring members of a social network as job candidates are described. In some examples, the systems and methods receive information associated with a job or a company associated with a job, identify members of a social network based on attributes for the members, and perform an action (e.g., send an email or update a widget on a profile page) associated with a member of the social network that is connected to the identified members and affiliated with the company. | 05-15-2014 |
20140143163 | USER CHARACTERISTICS-BASED SPONSORED JOB POSTINGS - A system may include a network interface, a user interface, and a recommendation engine. The user interface may be configured to receive a job characteristic of a job profile of a job posted to the social network and a job bid from an entity related to job to the social network. The recommendation engine may be configured to determine an aggregate job score for the user based on a relevance of the job characteristic to a user characteristic and the job bid. The network interface may be configured to transmit a message related to the job to the user based, at least in part, on the aggregate job score. | 05-22-2014 |
20140143164 | TECHNIQUES FOR QUANTIFYING THE JOB-SEEKING PROPENSITY OF MEMBERS OF A SOCIAL NETWORK SERVICE - Techniques are described herein for deriving, for each member of a social network service, a metric representing the job-seeking propensity of the member. Additionally, techniques for classifying each member with a job-seeking status (e.g., active job-seeker, passive job-seeker, or non-job-seeker) are described. A score-generating algorithm will analyze a variety of input data—including member profile data, social graph data, and activity or behavior data—to derive a job-seeker score, representing the job-seeking propensity of a member. | 05-22-2014 |
20140143165 | CUSTOMIZING A USER-EXPERIENCE BASED ON A JOB-SEEKER SCORE - Techniques are described herein for deriving, for each member of a social network service, a metric representing the job-seeking propensity of the member. Additionally, techniques for classifying each member with a job-seeking status (e.g., active job-seeker, passive job-seeker, or non-job-seeker) are described. A score-generating algorithm will analyze a variety of input data—including member profile data, social graph data, and activity or behavior data—to derive a job-seeker score, representing the job-seeking propensity of a member. Once derived, the metric is used to customize, personalize or otherwise tailor a user-experience. | 05-22-2014 |
20140143323 | USER CHARACTERISTICS-BASED SPONSORED COMPANY POSTINGS - A system may include a network interface, a user interface, and a recommendation engine. The user interface may be configured to receive a company characteristic of a company profile of a company posted to the social network and a company bid from an entity related to company to the social network. The recommendation engine may be configured to determine an aggregate company score for the user based on a relevance of the company characteristic to a user characteristic and the company bid. The network interface may be configured to transmit a message related to the company to the user based, at least in part, on the aggregate company score. | 05-22-2014 |
20140149328 | EVALUATION OF A RECOMMENDER - A machine may implement a recommender that provides recommendations to users. The machine may be configured to present a first version of the recommender configured by various parameters. A user may submit a message to the machine, and the machine may identify a parameter among the various parameters by tokenizing the message and identifying the parameter among the tokens. The machine may then generate a second version of the recommender by modifying the parameter and configuring the second version according to the modified parameter. The machine may then present the first and second versions of the recommender contemporaneously two different portions of the users. By tokenizing a further message received from the users, the machine may evaluate the first and second versions and determine whether the second version is a replacement of the first version. | 05-29-2014 |
20140195549 | SUGGESTED OUT OF NETWORK COMMUNICATION RECIPIENTS - Disclosed in some examples are methods, systems and machine readable medium for recommending an out-of-network communication by determining a set of potential recommended members of a social networking service based upon one or more recommendation criteria. In some examples the recommendation criteria may include: a profile similarity to a previous target of an out-of-network communication, a degree of correspondence between an interest and intent of the sending member, and a likelihood of response. | 07-10-2014 |
20140244612 | TECHNIQUES FOR QUANTIFYING THE INTENT AND INTERESTS OF MEMBERS OF A SOCIAL NETWORKING SERVICE - Techniques are described herein for deriving, for each member of a social networking service, a set of metrics representing a measure of the member's intent and interests. For example, a set of member-intent and member-interest scores are derived by detecting which of several applications and services that a particular user interacts with, when the interactions occur, the frequency of the interactions, the particular type of interactions, the nature of the any particular content (e.g., subject matter, topic, etc.) with which the member is interacting, and so forth. The member-intent and member-interest scores are then made available to a wide-variety of applications and services, for example, for use in personalizing various experiences to best suit the intent and interests of each member. | 08-28-2014 |
20150081576 | GENERATING A SUPPLEMENTAL DESCRIPTION OF AN ENTITY - A statistically overrepresented token in the descriptions of users associated with a target entity may be descriptive of the target entity. This may be true regardless of whether a primary description of the entity includes the overrepresented token. Accordingly, the entity description machine may access multiple descriptions of multiple users associated with the target entity. A portion of the multiple descriptions may each include a token descriptive of the target entity and of a subset of the multiple users. The entity description machine may determine that the token is overrepresented among the tokens within the multiple descriptions and generate a supplemental description of the target entity, where the supplemental description includes the overrepresented token. Once the supplemental description is generated, the entity description machine may use the supplemental description in referencing the target entity. | 03-19-2015 |
Patent application number | Description | Published |
20090091322 | Single-shot magnetic resonance spectroscopic imaging with partial parallel imaging - The present invention has a magnetic resonance spectroscopic imaging (MRSI) method that allows collecting a complete spectroscopic image with one spectral dimension and up to three spatial dimensions in a single signal excitation. The method employs echo-planar spatial-spectral encoding combined with phase encoding interleaved into the echo-planar readout train and partial parallel imaging to reconstruct spatially localized absorption mode spectra. This approach enables flexible tradeoff between gradient and RF encoding to maximize spectral width and spatial resolution. Partial parallel imaging (e.g. SENSE or GRAPPA) is employed with this methodology to accelerate the phase encoding dimension. A preferred implementation is with the recently developed superresolution parallel MRI method, which accelerates along both the readout and phase encoding dimensions and thus enables particularly large spectral width and spatial resolution. The symmetrical k-space trajectory of this methodology is designed to compensate phase errors due to convolution of spatial and spectral encoding. This method is suitable for hyperpolarized MRSI, spatial mapping of the diffusion coefficients of biochemicals and functional MRI using quantitative mapping of water relaxation. | 04-09-2009 |
20090285463 | Superresolution parallel magnetic resonance imaging - The present invention includes a method for parallel magnetic resonance imaging termed Superresolution Sensitivity Encoding (SURE-SENSE) and its application to functional and spectroscopic magnetic resonance imaging. SURE-SENSE acceleration is performed by acquiring only the central region of k-space instead of increasing the sampling distance over the complete k-space matrix and reconstruction is explicitly based on intra-voxel coil sensitivity variation. SURE-SENSE image reconstruction is formulated as a superresolution imaging problem where a collection of low resolution images acquired with multiple receiver coils are combined into a single image with higher spatial resolution using coil sensitivity maps acquired with high spatial resolution. The effective acceleration of conventional gradient encoding is given by the gain in spatial resolution Since SURE-SENSE is an ill-posed inverse problem, Tikhonov regularization is employed to control noise amplification. Unlike standard SENSE, SURE-SENSE allows acceleration along all encoding directions. | 11-19-2009 |
20110221439 | Magnetic resonance spectroscopy with real-time correction of motion and frequency drift, and real-time shimming - Disclosed are MR Spectroscopy and MR Spectroscopic Imaging (MRSI) methods comprising the sequential steps of water suppression, spatial prelocalization and spatial-spectral encoding, wherein the water suppression is modified to additionally measure and correct the frequency drift, the change in magnetic field inhomogeneity in the volume of interest, and the object movement. By inserting between the water suppression RF pulse and the dephasing gradient pulses either a phase sensitive MRI encoding module, or a 1D, 2D or 3D high-speed MRSI encoding module with simultaneous acquisition of the decaying water signal it is possible to measure frequency drift, magnetic field inhomogeneity and object movement. This information is used to dynamically change the synthesizer frequency of the scanner, the shim settings and to rotate the encoded k-space. In the preferred implementation this information is computed in real-time during the ongoing scan and via feeback loop downloaded to the acquisition control unit to update the aforementioned parameters before the subsequent data acquisition. | 09-15-2011 |
20120197104 | SYSTEM AND METHODS FOR AUTOMATIC PLACEMENT OF SPATIAL SUPRESSION REGIONS IN MRI AND MRSI - A system and methods for imaging a patient organ. The system includes a MRI imaging apparatus communicating with a memory and processor. The method aligns the organ with a standardized organ, and includes a step of spatially normalizing the standardized organ to the patient organ. The method also provides optimized slices of the standardized organ and translates optimized slices of standardized organ into optimized slices of the patient organ. The method images the patient organ according to the optimized slices of the patient organ. | 08-02-2012 |
20140343399 | Seed-Based Connectivity Analysis in Functional MRI - Functional MRI (fMRI) methods are presented for utilizing a magnetic resonance tomograph to map connectivity between brain areas in the resting state in real-time without the use of regression of confounding signal changes. They encompass: (a) iterative computation of the sliding window correlation between the signal time courses in a seed region and each voxel of an fMRI image series, (b) Fisher Z-transformation of each correlation map, (c) computation of a running mean and a running standard deviation of the Z-maps across a second sliding window to produce a series of meta mean maps and a series of meta standard deviation maps, and (d) thresholding of the meta maps. This methodology can be combined with regression of confounding signals within the sliding window. It is also applicable to task-based real-time fMRI, if the location of at least one task-activated voxel is known. | 11-20-2014 |