Abstract: Balancing content distribution between a machine learning model and a statistical model provides a baseline assurance in combination with the benefits of a well-trained machine learning model for content selection. In some implementations, a server receiving requests for a content item assigns a first proportion of the received requests to a first group and assigns remaining requests to a second group. The server uses a machine learning model to select variations of the requested content item for responding to requests assigned to the first group and uses a statistical model to select content variations for requests assigned to the second group. The server obtains performance information, e.g., acceptance rates for the different variations, and compares performance of the different models used for content selection. Audience share assigned to the machine learning model is increased when it outperforms the statistical model and decreased when it underperforms the statistical model.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: A system, device, and method may include a network interface device configured to be communicatively coupled to a user interface. An electronic data storage may be configured to store social network data related to users having accessed a social network content item A processor, coupled to the network interface device and the electronic data storage, may be configured to identify a relationship among at least some of the users, determine a relevance of the relationship to a member of the social network associated with the social network content item based, at least in part, on a social network profile of the member and social network profiles of the users, and cause the network interface device to display, on the user interface, information related to the relationship on the user interface based, at least in part, on the relevance.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: The disclosed subject matter relates to the delivery of hydroxyl-containing compounds as microparticles for a variety of pharmaceutical, biomedical, cosmetics and personal care applications. This entails the manufacture and use of polymerized hydro-X compounds. Note is made of hydro-X compounds selected from the group consisting of curcuminoids, stilbenoids, resolvins, phenylethanoids, tocopherols, tocotrienols, flavanones, flavones, prenylflavonoids, isoflavones, isoflavanes, dihydrochalcones, isoflavenes, coumestans, lignans, flavonoligans, flavonols, mycoestrogens, xenoestrogens, phytoestrogens, sterols, corticosteroids, androgens, estrogens, stanols, steroids, secosteroids, tannins, statins, catechols, catechins, opioids, cannabinoids, pleuromutilins, luteolinidin, anthocyanidins, apigeninidin, glycosylated compounds, and macrolides.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein to a Group Relevance Engine that generates, for a group in a social network, an aggregate group feature based on a common attribute shared amongst member accounts currently subscribed to the group. The Group Relevance Engine identifies an account feature corresponding to the common attribute in a profile of a target member account. The Group Relevance calculates a relevance score based at least on a match between the aggregate group feature and the account feature. The Group Relevance determines whether to recommend the group to the target member account based at least on the relevance score.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are described herein to a Discussion Relevance Engine that filters a plurality of discussions in a social network to identify a discussion pool. The Discussion Relevance Engine identifies a plurality of eligible discussions in the discussion pool, wherein each eligible discussion corresponds to a respective social network member group to which a target member account has previously subscribed. The Discussion Relevance Engine calculates, for each eligible discussion, a relevance score predictive of a relevance of the eligible discussion to the target member account. The Discussion Relevance Engine recommends at least one of the eligible discussions to the target member account based at least in part on the calculated relevance scores.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method are directed to a Digest Engine that identifies a feature(s) that is predictive of relevance, to a target member account in a professional social network, of content from a member group(s) to which the target member account is subscribed. Based on the feature(s), the Digest Engine determines a portion(s) of relevant content created amongst respective member accounts subscribed to the member group(s). The Digest Engine generates a persistent message providing access to the portion(s) of relevant content. The Digest Engine sends the persistent message to the target member account.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: A device, system, and method may include an electronic data storage configured to store social network data related to use of the social network by users. A processor, coupled to the electronic data storage, may be configured to determine a recommended action that a member of the social network may take to increase a likelihood of at least one of the uses of the social network to access a social network content item related to the member and determine an estimated statistical change in a rate at which the users may access the social network content item if the recommended action were implemented by the member based, at least in part, on the social network data stored in the electronic data storage.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.

Abstract: Techniques for discovering and recruiting team members for a team are described. According to various embodiments, a user request to identify one or more potential team members of a team is received, the user request including a user specification of a specific job title Skill mapping information identifying various sample skills associated with various sample job titles is accessed, and one or more specific skills associated with the specific job title is determined based on the skill mapping information. Thereafter, candidate team members of the team are identified from among members of a social network service having one or more of the specific skills.

Abstract: A system, device, and method may include a network interface device configured to be communicatively coupled to a user interface. An electronic data storage may be configured to store social network data related to users having accessed a social network content item A processor, coupled to the network interface device and the electronic data storage, may be configured to identify a relationship among at least some of the users, determine a relevance of the relationship to a member of the social network associated with the social network content item based, at least in part, on a social network profile of the member and social network profiles of the users, and cause the network interface device to display, on the user interface, information related to the relationship on the user interface based, at least in part, on the relevance.

Abstract: A device, system, and method may include a network interface device configured to be coupled to a user interface. An electronic data storage may be configured to store social network data. A processor, coupled to the network interface device and the electronic data storage, may be configured to cause the network interface device to display, on the user interface, social network content items, cause the network interface device to display, on the user interface, recommended actions related to the social network and a member of the social network associated with the user interface, the recommended actions being implementable based on a user input via the user interface, the recommended actions being displayed based on at least one display characteristic, and iteratively update the display characteristic based, at least in part, on an implementation, by the user, of at least one of the recommended actions.

Abstract: A device, system, and method may include an electronic data storage configured to store social network data related to use of the social network by users.

Abstract: Disclosed in some examples is a method comprising determining a first set of high ranking skills, the first set containing skills possessed by a member of the social networking service based upon the member's user profile; determining a second set of high ranking skills, the second set containing skills for a second member of the social networking service based on the second member's user profile; determining a third set of high ranking skills, the third set being the intersection between the first and second set of high ranking skills; and suggesting one or more of the skills in the third set of high ranking skills to the member for endorsement of the second member with respect to that skill.