Abstract: A method of delivering content includes receiving an interest packet including a plurality of requests in a content-centric networking (CCN), determining an availability of content for a first request among the plurality of requests in a content store (CS), fetching available pieces of content from the CS for a set of sequential requests starting from the first request among the plurality of requests in response to the content for the first request being available in the CS, the fetching comprising fetching available content for each remaining request subsequent to the first request among the sequential requests based on information from content identified for a request immediately preceding each remaining request, and delivering the fetched available pieces of content.

Abstract: A tracking system determines that a first device of an owner of a tracking device is not within a proximity of the tracking device, that a second device is within a proximity of the tracking device, and whether a tracking application is not running on the first device. Responsive to determining that the tracking application is not running on the first device, the tracking system generates a notification informing the owner that the tracking application is not running on the first device. Responsive to determining that a location of the second device within a proximity of the tracking device is more than a threshold distance from a last known location of the tracking device, the tracking system generates a another notification informing the owner that the tracking device may be lost. The tracking system provides one or both of the notifications to the first device for display to the owner.

Abstract: A tracking system determines that a first device of an owner of a tracking device is not within a proximity of the tracking device, that a second device is within a proximity of the tracking device, and whether a tracking application is not running on the first device. Responsive to determining that the tracking application is not running on the first device, the tracking system generates a notification informing the owner that the tracking application is not running on the first device. Responsive to determining that a location of the second device within a proximity of the tracking device is more than a threshold distance from a last known location of the tracking device, the tracking system generates a another notification informing the owner that the tracking device may be lost. The tracking system provides one or both of the notifications to the first device for display to the owner.

Abstract: An approach is provided for remotely controlling set-top boxes. A command is received from a computing device for controlling a plurality of set-top boxes. The set-top boxes are configured according to the received command.

Abstract: A system, a machine-readable storage medium storing instructions, and a computer-implemented method as described herein are directed to a Sales Lead Engine that links external data to social network data from a social network service. The Sales Lead Engine determines the external data and the social network data satisfy a sales lead criterion. The Sales Lead Engine identifies an organization account in the social network service identified by the external data and the social network data. The Sales Lead Engine provides a sales lead notification to a target member account based on a selection by the target member account to follow the organization account in the social network service.

Abstract: System and methods for generating a shareability score in accordance with some example embodiments are disclosed. A social networking system receives a request to generate a shareability score for a list of content items for an organization. The social networking system identifies a plurality of members associated with the organization and analyzes past share data for the plurality of members to generate an organization sharing profile. The social networking system retrieves early sharing information for each content item in the list of content items. The social networking system generates a shareability score for each particular content item and ranks the list of content items based on the generated shareability scores. The social networking system then transmits the ranked list of content items to a client device, receives a selection of one or more content items, and broadcasts the one or more selected items to a plurality of client devices.

Abstract: 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.

Abstract: In an example embodiment, a query for search results is received, the query including at least one value for one facet, a facet defining a categorical dimension for the search results. It is then determined that the facet in the query is exclusive. In response to the determination that the facet is exclusive: for each potential facet different from the facet in the query: for each potential value in the potential facet: conditional entropy gain of the value in the query and the potential value is determined. The potential value in the potential facet that has the highest conditional entropy gain is determined, as is the potential facet with the minimum maximum conditional entropy gain. Then the potential facet with the minimum maximum is input into a machine learning model, causing the machine learning model to output one or more suggested facets to add to the query.

Abstract: In an example embodiment, one or more specified ideal candidates are used to perform a search in a database. One or more attributes are extracted from one or more ideal candidate member profiles. A search query is then generated based on the extracted one or more attributes. Then, a search is performed on member profiles in the social networking service using the generated search query, returning one or more result member profiles.

Abstract: In an example embodiment, one or more sample ideal candidate member profiles in a social networking service are obtained, as well as one or more sample search result member profiles in the social networking service. Then, for each unique pair of sample ideal candidate member profile and sample search result member profile, a label is generated using a score generated from log information of the social networking service, the log information including records of communications between a searcher and members of the social networking service, the score being higher if the searcher communicated with both the member corresponding sample ideal candidate member profile and the member corresponding to the sample search result member profile in a same search session. The generated labels are fed into a machine learning algorithm to train a combined ranking model used to output ranking scores for search result member profiles.

Abstract: In an example embodiment, as time goes on and as refinements are received to an online search, weights assigned to each of the one or more query-based features are dynamically trained to increase as more refinements are received and weights assigned to each of the one or more ideal candidate-based features to decrease as more refinements are received.

Abstract: In an example embodiment, one or more ideal candidate member profiles in a social networking service are obtained. Then a search is performed on member profiles in the social networking service using a search query, returning one or more result member profiles. One or more query-based features are produced from the one or more result member profiles using the search query. One or more ideal candidate-based features are produced from the one or more result member profiles using the one or more ideal candidate member profiles. The one or more query-based features and the one or more ideal candidate-based features are input to a combined ranking model trained by a machine learning algorithm to output a ranking score for each of the one or more result member profiles. The one or more result member profiles are then ranked based on the ranking scores.

Abstract: 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.

Abstract: Techniques for searching for future candidates are disclosed herein. In some example embodiments, a future candidate system determines one or more target candidate attributes based on user input, and identifies one or more precedent candidate attributes based on a sequential relationship between the one or more precedent candidate attributes and the one or more target candidate attributes, with the one or more precedent candidate attributes being different from and preceding the one or more target candidate attributes. In some example embodiments, the future candidate system identifies one or more candidates from among a plurality of candidates based on a determination that the one or more candidates comprise the one or more precedent candidate attributes, and causes the identified one or more candidates to be displayed on a client device.

Abstract: The subject disclosure is directed towards using primary data deduplication concepts for more efficient access of data via content addressable caches. Chunks of data, such as deduplicated data chunks, are maintained in a fast access client-side cache, such as containing chunks based upon access patterns. The chunked content is content addressable via a hash or other unique identifier of that content in the system. When a chunk is needed, the client-side cache (or caches) is checked for the chunk before going to a file server for the chunk. The file server may likewise maintain content addressable (chunk) caches. Also described are cache maintenance, management and organization, including pre-populating caches with chunks, as well as using RAM and/or solid-state storage device caches.

Abstract: A first user of a presentation machine may be a recruiter that initiates an action in reference to a first user profile. The first user profile may describe a first candidate for a job. The presentation machine may identify the first user profile and determine a similarity score that indicates a degree of similarity between the first user profile and a second user profile that describes a second candidate for the job. The presentation machine may also access a volatility score that indicates a likelihood that the second candidate is receptive to a proposal that the second candidate be employed by an employer. Based on the similarity score and on the volatility score, the presentation machine may determine a rank of the second user profile. Based on the determined rank, the presentation machine may present the second user profile to the first user.

Abstract: The present invention relates to textile fabrics and methods of manufacturing textile fabrics. Particularly, the invention comprises a method of producing a fabric, comprising the steps of (i) blending chemo mechanically felting fibers with non-felting fibers into a blended feed material, (ii) spinning the blended feed material into a blended yarn, (iii) producing a fabric comprising the blended yarn, (iv) subjecting the fabric to a first fabric treatment comprising a mechanical felting treatment; and (v) subjecting the fabric to a second fabric treatment comprising a chemical treatment of the fabric with an alkali, wherein the ratio of weight of the alkali to dry fabric weight is between 0.02 and 0.05, thereby obtaining increased air space in the resultant fabric.

Abstract: An article of dynamic jewellery includes a protective housing having an interior and a viewing window through which the interior is visible. A pendulum is suspended within the interior of the protective housing. The lower end of the pendulum supports an ornament which gives the pendulum sufficient weight that the pendulum swings freely in response to movements of a wearer's body.

Abstract: 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.

Abstract: System and techniques for facet expansion are described herein. A user interface element may be presented on facet selection portion of a search result display including search results. Here, the user interface element is arranged to accept user input of a facet. Partial user input for a facet may be received. A peer entity to an entity corresponding to the facet may be obtained. A peer facet may be presented in a suggestion element in the facet selection portion in response to receiving the partial user input.