Abstract: A request from a user to view a video content item may be received, the requesting user being associated with at least one of a set of preferences or a context. group of similar users may be identified based the set of preferences or the context. A number of candidate video items corresponding to the video content item may be identified. A watch time difference may be determined for each candidate video item of the number of candidate video items. A subset may be determined based on the watch time difference associated with each candidate video items. The candidate video items in the subset may be ranked based on an activity rate associated with the corresponding candidate video item. A candidate video item with the highest ranking may be provided to the user.

Abstract: A request from a user to view a video content item may be received, the requesting user being associated with a set of preferences and a context. A group of similar users may be identified based the set of preferences or the context. A number of promotional video items corresponding to the video content item may be identified. A first subset of the number of promotional video items may be determined based on the set of preferences or the context of the user. A watch time difference may be determined for each promotional video item in the first subset. A second subset may be determined based on the watch time difference associated with each promotional video items. An activity rate associated with the promotional video items in the second subset is determined. A promotional video item of the second subset that satisfies a criterion is provided to the user.

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 request from a user to view a video content item may be received, the requesting user being associated with a set of preferences and a context. A group of similar users may be identified based the set of preferences or the context. A number of promotional video items corresponding to the video content item may be identified. A first subset of the number of promotional video items may be determined based on the set of preferences or the context of the user. A watch time difference may be determined for each promotional video item in the first subset. A second subset may be determined based on the watch time difference associated with each promotional video items. An activity rate associated with the promotional video items in the second subset is determined. A promotional video item of the second subset that satisfies a criterion is provided to the user.

Abstract: The disclosure provides a method for document management in a network. The method includes acquiring, by an electronic device, a source document as an image, extracting, by the electronic device, a plurality of multi-modal information from the source document by parsing the source document, automatically determining, by the electronic device, a category of the source document based on a comparison of the extracted plurality of multi-modal information with a plurality of pre-defined features, extracting, by the electronic device, a plurality of data fields corresponding to the determined category from the source document, determining, by the electronic device, a priority for each of the plurality of data fields and storing, by the electronic device, the plurality of data fields in at least one of a secure information source and an unsecure information source based on the determined priority.

Abstract: A request from a user to view a video content item may be received, the requesting user being associated with a set of preferences and a context. A group of similar users may be identified based at least one of: one or more preferences in the set of preferences or the context. A first promotional video item corresponding to the video content item may be identified. A first watch time value for a first portion of the group of similar users may be determined based on an amount of time during a period of time that users of the first portion of the group have viewed the video content item after being provided the first promotional video item. A second watch time value for a second portion of the group of similar users may be determined based on an amount of time during the period of time that the users of the second portion of the group have viewed the video content item, the first promotional video item not provided to the users of the second portion of the group.

Abstract: The present disclosure relates to packaging boxes for toy cars. The packaging box of the present disclosure serves a dual purpose, firstly for packaging the toy car and secondly, the packaging box serves as an accessory for the toy car. The packaging box comprises a container element and a lid element, each comprising at least one upright longitudinal sidewall and at least one lateral foldable sidewall, wherein the longitudinal sidewall and the foldable sidewall of the container element and the lid element engage with each other defining a track, which can be employed for displacing the toy car thereon.

Abstract: A request from a user to view a video content item may be received, the requesting user being associated with a set of preferences and a context. A group of similar users may be identified based at least one of: one or more preferences in the set of preferences or the context. A first promotional video item corresponding to the video content item may be identified. A first watch time value for a first portion of the group of similar users may be determined based on an amount of time during a period of time that users of the first portion of the group have viewed the video content item after being provided the first promotional video item. A second watch time value for a second portion of the group of similar users may be determined based on an amount of time during the period of time that the users of the second portion of the group have viewed the video content item, the first promotional video item not provided to the users of the second portion of the group.

Abstract: A promotional message may be provided to a first portion of a group of users. A first watch time may be identified based on an amount of time during a period of time that users of the first portion view the video content items after being provided the promotional message. A second watch time may be identified based on an amount of time during the period of time that users of a second portion of the group view video content items where the promotional message is not provided to the users of the second portion of the group. A difference between the first watch time and the second watch time may be calculated. A determination of whether to provide the promotional message to a subsequent user sharing one or more characteristics with the group of users may be based on the difference between the first watch time and the second watch time may be made.

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 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 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 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.