Abstract: Provided are methods and computer-readable media for providing recommended entities based on a user's external social graph, such as asymmetric social graph of a social networking service. In some embodiments, entities responsive to a search query or other request may be obtained. Each entity may be evaluated to determine if the entity is associated with a contact from a user's social graph. The association may include an evaluation (e.g., a rating, review, other evaluation or combination thereof) of the entity by the contact. Additionally, the contacts having associations with an entity may be ranked based on a relationship score with a user. The entities having associations with the contacts from a user's social graph may be provided as recommended entities to the user, and the association may be annotated to the recommended entity for viewing by the user.

Abstract: A method and devices for configuring a data transmission network are disclosed.

Abstract: An apparatus, method and computer program is described comprising receiving data at a receiver of a transmission system; using a receiver algorithm to convert data received at the receiver into an estimate of the first coded data, the receiver algorithm having one or more trainable parameters; generating an estimate of first data bits by decoding the estimate of the first coded data, said decoding making use of an error correction code of said encoding of the first data bits; generating a refined estimate of the first coded data by encoding the estimate of the first data bits; generating a loss function based on a function of the refined estimate of the first coded data and the estimate of the first coded data; updating the trainable parameters of the receiver algorithm in order to minimise the loss function; and controlling a repetition of updating the trainable parameters by generating, for each repetition, for the same received data, a further refined estimate of the first coded data, a further loss functi

Abstract: An apparatus, computer program and method is described including receiving data at a receiver of a communication system, generating an estimate of the data as transmitted by a transmitter of the transmission system (wherein generating the estimate includes a receiver algorithm having at least some trainable weights), generating a refined estimate of the transmitted data, based on said estimate and an error correction algorithm (wherein, in an operational mode, said estimate of the data as transmitted is generated based on the received data and said refined estimate); and generating, in the operational mode, a revised estimate of the transmitted data on each of a plurality of iterations of said generating an estimate of the transmitted data until a first condition is reached.

Abstract: An apparatus, method and computer program is described comprising receiving data at a receiver of a transmission system; using a receiver algorithm to convert data received at the receiver into an estimate of the first coded data, the receiver algorithm having one or more trainable parameters; generating an estimate of first data bits by decoding the estimate of the first coded data, said decoding making use of an error correction code of said encoding of the first data bits; generating a refined estimate of the first coded data by encoding the estimate of the first data bits; generating a loss function based on a function of the refined estimate of the first coded data and the estimate of the first coded data; updating the trainable parameters of the receiver algorithm in order to minimise the loss function; and controlling a repetition of updating the trainable parameters by generating, for each repetition, for the same received data, a further refined estimate of the first coded data, a further loss functi

Abstract: A method and devices for configuring a data transmission network are disclosed.

Abstract: A group recommendation provides end users in a social group a set of recommended destinations based on the combined personal preferences of the members of the social group. Members of a social group are identified using a combination of location based signals and social graph information in response to receiving a recommendation request. The group recommendation may be determined by combining the personal preferences associated with each member of the group into a master preference profile. Alternatively, the group recommendation may be determined by first calculating an individual recommendation list for each member of the social group and then calculating a composite score for each recommendation on the individual recommendation lists.

Abstract: A group recommendation provides end users in a social group a set of recommended destinations based on the combined personal preferences of the members of the social group. Members of a social group are identified using a combination of location based signals and social graph information in response to receiving a recommendation request. The group recommendation may be determined by combining the personal preferences associated with each member of the group into a master preference profile. Alternatively, the group recommendation may be determined by first calculating an individual recommendation list for each member of the social group and then calculating a composite score for each recommendation on the individual recommendation lists.

Abstract: Provided are methods and computer-readable media for providing recommended entities based on a user's external social graph, such as asymmetric social graph of a social networking service. In some embodiments, entities responsive to a search query or other request may be obtained. Each entity may be evaluated to determine if the entity is associated with a contact from a user's social graph. The association may include an evaluation (e.g., a rating, review, other evaluation or combination thereof) of the entity by the contact. Additionally, the contacts having associations with an entity may be ranked based on a relationship score with a user. The entities having associations with the contacts from a user's social graph may be provided as recommended entities to the user, and the association may be annotated to the recommended entity for viewing by the user.

Abstract: A group recommendation provides end users in a social group a set of recommended destinations based on the combined personal preferences of the members of the social group. Members of a social group are identified using a combination of location based signals and social graph information in response to receiving a recommendation request. The group recommendation may be determined by combining the personal preferences associated with each member of the group into a master preference profile. Alternatively, the group recommendation may be determined by first calculating an individual recommendation list for each member of the social group and then calculating a composite score for each recommendation on the individual recommendation lists.

Abstract: A group recommendation provides end users in a social group a set of recommended destinations based on the combined personal preferences of the members of the social group. Members of a social group are identified using a combination of location based signals and social graph information in response to receiving a recommendation request. The group recommendation may be determined by combining the personal preferences associated with each member of the group into a master preference profile. Alternatively, the group recommendation may be determined by first calculating an individual recommendation list for each member of the social group and then calculating a composite score for each recommendation on the individual recommendation lists.

Abstract: A system and method for providing destination recommendations to a user based on mining of a location history. The location history provides information on locations visited by users of the system over time. The system mines the location history to identify location pairs. Each location pair comprises an originating location visited by a user and a next location that was visited by the user within a defined time threshold of visiting the originating location. The system aggregates location pairs by common originating location. The system then takes into account the current location of a requesting user. The system uses the current location information to identify a corresponding originating location in a location history index. The system provides recommendations based at least in part on how frequently certain next locations were visited after visiting the originating location.

Abstract: A group recommendation provides end users in a social group a set of recommended destinations based on the combined personal preferences of the members of the social group. Members of a social group are identified using a combination of location based signals and social graph information in response to receiving a recommendation request. The group recommendation may be determined by combining the personal preferences associated with each member of the group into a master preference profile. Alternatively, the group recommendation may be determined by first calculating an individual recommendation list for each member of the social group and then calculating a composite score for each recommendation on the individual recommendation lists.

Abstract: Provided are methods and computer-readable media for providing recommended entities based on a user's external social graph, such as asymmetric social graph of a social networking service. In some embodiments, entities responsive to a search query or other request may be obtained. Each entity may be evaluated to determine if the entity is associated with a contact from a user's social graph. The association may include an evaluation (e.g., a rating, review, other evaluation or combination thereof) of the entity by the contact. Additionally, the contacts having associations with an entity may be ranked based on a relationship score with a user. The entities having associations with the contacts from a user's social graph may be provided as recommended entities to the user, and the association may be annotated to the recommended entity for viewing by the user.