Abstract: Disclosed herein is a nutritional supplement containing apple cider vinegar (ACV), including compositions, formulations, and combinations of ingredients in the ACV nutritional supplement, as well as processes for manufacturing these supplements. The disclosed nutritional supplement can include ACV, a gelling agent such as pectin or gelatin, an oligosaccharide, a disaccharide, and water.

Abstract: Disclosed herein is a nutritional supplement containing apple cider vinegar (ACV), including compositions, formulations, and combinations of ingredients in the ACV nutritional supplement, as well as processes for manufacturing these supplements. The disclosed nutritional supplement can include ACV, a gelling agent such as pectin or gelatin, an oligosaccharide, a disaccharide, and water.

Abstract: Disclosed herein is a nutritional supplement containing apple cider vinegar (ACV), including compositions, formulations, and combinations of ingredients in the ACV nutritional supplement, as well as processes for manufacturing these supplements. The disclosed nutritional supplement can include ACV, a gelling agent such as pectin or gelatin, an oligosaccharide, a disaccharide, and water.

Abstract: According to an embodiment, there is provided an electronic device comprising: a memory storing instructions; and at least one processor configured to execute the instructions to: generate state information regarding a device state of the electronic device of a first user and communication information regarding communications of the first user with a second user; transmitting the state information and the communication information to a server or an electronic device of the second user, wherein the state information and the communication information are used to determine communication availability of the first user and to provide the second user with information regarding the communication availability of the first user.

Abstract: A computerized method for authenticating access to a subscription-based service to detect an attempted cyber-attack. The method features operations by the cloud broker that include receiving service policy level information and information based on operational metadata. The service policy level information includes at least subscription attributes to identify one or more performance criterion in analyses conducted on one or more objects submitted by a sensor for malware representing an attempted cyber-attack. The operational metadata includes metadata that pertains to an operating state of one or more clusters of a plurality of clusters of the subscription-based service. The cloud broker, using both the service policy level information and the information based on the operational metadata, selecting a cluster of the plurality of clusters to analyze the one or more objects submitted by the sensor and establishes a communication session between the sensor and the cluster via the cloud broker.

Abstract: Shown herein is a nutritional supplement containing apple cider vinegar (ACV), including compositions, formulations, and combinations of ingredients in the ACV nutritional supplement, as well as processes for manufacturing these supplements. The nutritional supplement can include ACV, a gelling agent such as pectin or gelatin, an oligosaccharide, a disaccharide, and water.

Abstract: A system and method for intermediate landing page rerouting are provided. In example embodiments, determine whether a webpage associated with a hyperlink has corresponding social network activities. Extract content from the webpage determined to have corresponding social network activities. In response to a selection of the hyperlink, reroute a web browser to an intermediate landing page. Cause presentation, at a user interface, of the extracted content and the corresponding social network activities.

Abstract: In an example embodiment, usage information is used to calculate one or more individual document historical information-deficient metrics (IDHIDMs) by combining values for the one or more metrics from multiple documents within the document corpus that share an identical combination of entities of the one or more entity types. A search query is segmented into a plurality of segments, wherein at least one of the plurality of segments is tagged as a first entity type and at least one of the plurality of segments is tagged as a second entity type. At least one for a combination of entities matching the tagged segments is used to rank one or more retrieved documents responsive to the query.

Abstract: A system and method may optional include or utilize a processor configured to receive a request for social network content for display in a sponsored content position in a newsfeed of a social network interface, the position having a position criterion, identify a sponsored content item of multiple sponsored content items stored on a database based, at least in part, on a characteristic of the sponsored content item meeting the position criterion, a bid associated with the sponsored content item, and a scaling factor, wherein each of the sponsored content items correspond to one of multiple item types and at least two of the sponsored content items are of a different item type. The scaling factor for each of the sponsored content items is based on the item type of the corresponding one of the sponsored content items.

Abstract: A system and method of adjusting an affinity score between an entity pair in a social network is disclosed. The method may include determining, with a processor, whether a first member of the entity pair is a heavy user member. The method further includes if the first member is the heavy user member, determining, with the processor, an affinity adjustment factor between the first member and the second member, and adjusting, with the processor, the affinity score between the first member and the second member of the entity pair in accordance with the adjustment factor to determine an adjusted affinity score. The method may include determining, with the processor, whether a number of interactions on content items indicates that the first member is the heavy user member. The second member is associated with a content item that is being considered for display to the first member.

Abstract: In an example embodiment, a machine learned model is used to determine whether to send a notification for a feed object to a user. This machine learned model is optimized not just based on the likelihood that the notification will cause the user to interact with the feed object, but also the likely short-term and long-term impacts of the user interacting with the feed object. This machine learned model factors in not only the viewer's probability of immediate action, such as clicking on a feed object, but also the probability of long-term impact, such as the display causing the viewer to contribute content to the network or the viewer's response encouraging more people to contribute content to the network. As such, the machine learned model is optimized not just on notification interactivity but also on feed objects interactivity.

Abstract: In an example, a set of cohort types and an anonymized set of confidential data data values for a plurality of cohorts having cohort types in the set of cohort types are obtained. Then it is determined, from a set of candidate data transformations, a best fitting data transformation for the anonmyized set of confidential data data values. The anonymized set of confidential data data values is transformed using the best fitting data transformation. Optimal smoothing parameters are computed for each cohort type. Then, for each cohort in the set of cohort types having a small sample size, a best parent for the cohort is determined and a posterior distribution for the cohort is determined based on the best parent for the cohort and the optimal smoothing parameters for a cohort type for the cohort.

Abstract: A system for processing data is provided. During operation, the system obtains a current window of one or more intervals of timeseries data collected from a monitored system. Next, the system continuously performs a statistical hypothesis test that compares the one or more intervals of the time-series data with baseline values from historic time-series data associated with the monitored system. When the statistical hypothesis test indicates a deviation of the time-series data from the baseline values, the system outputs an alert of an anomaly represented by the deviation.

Abstract: A system and method optionally includes or utilizes a processor may receive a request for social network content for display in a position of a plurality of sponsored content positions in a newsfeed of a social network interface, each of the plurality of sponsored content positions having a position criterion, at least two of the plurality of sponsored content positions having a different position criterion and identify a sponsored content item of a plurality of sponsored content items stored on a database based, at least in part, on a characteristic of the sponsored content item meeting the position criterion and a bid associated with the sponsored content item. A transmitter may transmit the sponsored content item from the processor to a server for display on a user interface.

Abstract: This disclosure relates to systems and methods that include a member activity database including data indicative of interactions with content items on a social network by a population of users of the social network. A processor is configured to obtain an optimization criterion based on at least two constraints related to a performance of the social network, obtain, for a subset of the population of users, at least some of the data indicative of interactions with content items from the member activity database, determine, based on the at least some of the data as obtained, an operating condition for the social network that is estimated to meet the optimization criterion, and provide, to at least some of the user devices via the network interface, the social network based, at least in part, on the operating condition.

Abstract: In an example, a plurality of member profiles in a social networking service are obtained, each member profile identifying a member and listing one or more skills the corresponding member has explicitly added to the member profile, the one or more skills indicating a proficiency by the member in the corresponding skill. A members-skills matrix is formed, wherein each cell in the matrix is assigned a value based on whether the corresponding member has the corresponding skill. The dot product of the members matrix and the skills matrix is then computed and used to identify one or more latent skills of a first member of the social networking service. Then a first digitally stored member profile is augmented with the one or more latent skills by combining the one or more latent skills with explicit skills for purposes of one or more searches that utilize member skills as an input variable.

Abstract: Iterations of a machine learned model training process are performed until a convergence occurs. A fixed effects machine learned model is trained using a first machine learning algorithm. Residuals of the training of the fixed effects machine learned model are determined by comparing results of the trained fixed effects machine learned model to a first set of target results. A first random effects machine learned model is trained using a second machine learning algorithm and the residuals of the training of the fixed effects machine learned model. Residuals of the training of the first random effect machine learned model are determined by comparing results of the trained first random effects machine learned model to a second set of target result, in each subsequent iteration the training of the fixed effects machine learned model uses residuals of the training of a last machine learned model trained in a previous iteration.

Abstract: In an example, predictions/recommendations using machine learned models are made even more accurate by using three models instead of a single Generalized Linear Mixed (GLMix) model. Specifically, rather than having a single GLMix model with different coefficients for users and items, three separate models are used and then combined. Each of these models has different granularities and dimensions. A global model models the similarity between user attributes (e.g., from the member profile or activity history) and item attributes. A per-user model models user attributes and activity history. A per-item model models item attributes and activity history. Such a model may be termed a Generalized Additive Mixed Effect (GAME) model.

Abstract: A stateful cluster may implement scaling of the stateful cluster while maintaining access to the state of the stateful cluster. A scaling event for a stateful cluster may be detected, and in response the stateful cluster may be adjusted to include a different number of nodes. The state of the cluster may then be logically distributed among the different number of nodes according to a monotone distribution scheme. The adjusted node may then service access requests according to the monotone distribution scheme. Prior to making the adjusted storage cluster available for servicing access requests, the nodes from the original cluster may still service access requests for state.

Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains a set of components of a time-series performance metric associated with an anomaly in a performance of one or more monitored systems. For each component in the set of components, the system performs a statistical hypothesis test on the component to assess a deviation of the component from a baseline value of the component. When the statistical hypothesis test identifies a statistically significant deviation of the component from the baseline value, the system outputs an alert comprising a root cause of the anomaly that is represented by the statistically significant deviation of the component from the baseline value.