Abstract: Techniques for improving a search user interface by demoting a set of spam user profiles included in a listing of candidate user profiles that are to be presented in response to a search request are disclosed herein. The search request is received from a client device. The search request requests the listing of candidate user profiles corresponding to a search query. The listing of candidate user profiles corresponding to the search query is determined. A trained spam detection model is applied to each of the candidate user profiles to identify the set of spam user profiles. The demoting of the spam user profiles is performed. The listing of candidate user profiles is communicated for presentation in the search user interface, the presentation reflecting the demoting of the spam user profiles.

Abstract: A method for determining specific conditions occurring on industrial equipment based upon received signal data from sensors attached to the industrial equipment is provided. Using a server computer system, signal data is received and aggregated into feature vectors. Feature vectors represent a set of signal data over a particular range of time. The feature vectors are clustered into subsets of feature vectors based upon attributes the feature vectors. One or more sample episodes are received, where a sample episode includes sample feature vectors and specific classification labels assigned to the sample feature vectors. A signal data model is created that includes the associated feature vectors, clusters, and assigned classification labels.

Abstract: Techniques for improving a search user interface by demoting a set of spam user profiles included in a listing of candidate user profiles that are to be presented in response to a search request are disclosed herein. The search request is received from a client device. The search request requests the listing of candidate user profiles corresponding to a search query. The listing of candidate user profiles corresponding to the search query is determined. A trained spam detection model is applied to each of the candidate user profiles to identify the set of spam user profiles. The demoting of the spam user profiles is performed. The listing of candidate user profiles is communicated for presentation in the search user interface, the presentation reflecting the demoting of the spam user profiles.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system obtains a set of member features associated with a member of a social network and a set of attribute features associated with a set of member attributes. Next, the system analyzes the member features and the attribute features to predict a propensity of the member to accept recommendations of the member attributes as profile edits to a member profile of the member. The system then uses the predicted propensity to output a subset of the member attributes as recommended profile edits to the member.

Abstract: Among other things, embodiments of the present disclosure discussed herein may be used to analyze the online social network profiles of users of the social network and generate customized summaries of the profiles. Among other things, the embodiments of the present disclosure help quickly and efficiently generate an intuitive and personalized summary of a user's profile, even where a user's profile contains a relatively lengthy amount of content.

Abstract: Among other things, embodiments of the present disclosure discussed herein may be used to analyze the online social network profiles of users of the social network and generate customized summaries of the profiles. Among other things, the embodiments of the present disclosure help quickly and efficiently generate an intuitive and personalized summary of a user's profile, even where a user's profile contains a relatively lengthy amount of content.

Abstract: Systems and methods for analyzing job listing data and member profile data to identify in demand skills is disclosed. A computer system receives a request for recommended job listings from a client device. The system accesses a plurality of job listings from a database. The system parses each of the job listings of the plurality of job listings to identify a list of skills required by each job listing. The system accesses a plurality of member profiles. The system analyzes the plurality of member profiles to extract a list of skills from each member profile. For a particular skill in the list of skills, the system calculates a first number of job listings requiring the particular skill and a first number of members who possess the particular skill. The system determines a skill gap value for the particular skill based on the number of job listings requiring that particular skill and the number of members who possess that particular skill.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system obtains user feedback associated with recommending a set of member attributes as profile edits to a set of members in a social network. Next, the system analyzes the user feedback to determine a set of acceptance rates of the member attributes. The system then uses the acceptance rates to update a taxonomy of the member attributes for use in improving recommendations of the member attributes to the members.

Abstract: The disclosed embodiments provide a system for improving use of a social network. During operation, the system obtains a set of member features associated with a member of a social network and a set of attribute features associated with a set of member attributes. Next, the system analyzes the member features and the attribute features to predict a propensity of the member to accept recommendations of the member attributes as profile edits to a member profile of the member. The system then uses the predicted propensity to output a subset of the member attributes as recommended profile edits to the member.

Abstract: A method for determining specific conditions occurring on industrial equipment based upon received signal data from sensors attached to the industrial equipment is provided. Using a server computer system, signal data is received and aggregated into feature vectors. Feature vectors represent a set of signal data over a particular range of time. The feature vectors are clustered into subsets of feature vectors based upon attributes the feature vectors. One or more sample episodes are received, where a sample episode includes sample feature vectors and specific classification labels assigned to the sample feature vectors. A signal data model is created that includes the associated feature vectors, clusters, and assigned classification labels.

Abstract: Embodiments of systems and methods for efficient broadcasting via random linear packet combining are described. A plurality of data packets are received from a data source according to embodiments. The plurality of data packets is divided into a plurality of data blocks, and bits associated with the plurality of data blocks are multiplied by a set of coefficients to generate a plurality of product values. An encoded data packet having a plurality of encoded data blocks may also be generated by linearly combining the plurality of product values for respective data blocks of each of the plurality of data packets into corresponding encoded data blocks of the encoded data packet. Because each encoded data packet includes information about a complete set of data packets, rather than just a subset, less broadcast redundancy may be required.

Abstract: Embodiments of systems and methods for efficient broadcasting via random linear packet combining are described. A method for random linear packet combining includes receiving a plurality of data packets from a data source. Additionally, the method may include dividing the plurality of data packets into a plurality of data blocks, and multiplying bits associated with the plurality of data blocks by a set of coefficients to generate a plurality of product values. The method may also include generating an encoded data packet having a plurality of encoded data blocks, wherein generating the encoded data packet comprises linearly combining the plurality of product values for respective data blocks of each of the plurality of data packets into corresponding encoded data blocks of the encoded data packet. Because each encoded data packet includes information about a complete set of data packets, rather than just a subset, less broadcast redundancy may be required.