Abstract: The invention relates to a computer-implemented method, a corresponding a computer program product and a corresponding apparatus for distributing cached content in a network, the computer-implemented method comprising: collecting statistics regarding requests made and paths taken by the requests from source nodes to server nodes via intermediate nodes, the source nodes, intermediate nodes, and server nodes interconnected by edges having queues with respective queue sizes associated therewith, the requests including indications of content items to be retrieved; storing the content items at the server nodes; caching, by the intermediate nodes, the content items up to a caching capacity; and performing caching decisions that determine which of the content items are to be cached at which of the intermediate nodes, based upon costs that are monotonic, non-decreasing functions of the sizes of the queues.

Abstract: Embodiments solve a problem of minimizing routing costs by jointly optimizing caching and routing decisions over an arbitrary network topology. Embodiments solve an equivalent caching gain maximization problem, and consider both source routing and hop-by-hop routing settings. The respective offline problems are non-deterministic polynomial time (NP)-hard. Nevertheless, embodiments show that there exist polynomial time approximation methods producing solutions within a constant approximation from the optimal. Embodiments herein include distributed, adaptive networks, computer methods, systems, and computer program products that provide guarantees of routing cost reduction. Simulation is performed over a broad array of different topologies. Embodiments reduce routing costs by several orders of magnitude compared to existing approaches, including existing approaches optimizing caching under fixed routing.

Abstract: The invention relates to a computer-implemented method, a corresponding a computer program product and a corresponding apparatus for distributing cached content in a network, the computer-implemented method comprising: collecting statistics regarding requests made and paths taken by the requests from source nodes to server nodes via intermediate nodes, the source nodes, intermediate nodes, and server nodes interconnected by edges having queues with respective queue sizes associated therewith, the requests including indications of content items to be retrieved; storing the content items at the server nodes; caching, by the intermediate nodes, the content items up to a caching capacity; and performing caching decisions that determine which of the content items are to be cached at which of the intermediate nodes, based upon costs that are monotonic, non-decreasing functions of the sizes of the queues.

Abstract: Embodiments solve a problem of minimizing routing costs by jointly optimizing caching and routing decisions over an arbitrary network topology. Embodiments solve an equivalent caching gain maximization problem, and consider both source routing and hop-by-hop routing settings. The respective offline problems are non-deterministic polynomial time (NP)-hard. Nevertheless, embodiments show that there exist polynomial time approximation methods producing solutions within a constant approximation from the optimal. Embodiments herein include distributed, adaptive networks, computer methods, systems, and computer program products that provide guarantees of routing cost reduction. Simulation is performed over a broad array of different topologies. Embodiments reduce routing costs by several orders of magnitude compared to existing approaches, including existing approaches optimizing caching under fixed routing.

Abstract: A content distribution network, including: a content server that stores a set of content items; a plurality of gateways for storing and serving content requests to a subset of the content items, the plurality of gateways being grouped into a plurality of classes of gateways; and a plurality of class trackers corresponding to the plurality of classes; wherein each class tracker manages a placement of content items and an assignment of content requests for its class of gateways; wherein the plurality of class trackers exchange congestion signals among themselves; wherein, for each content item, each class tracker determines a fraction of gateways in its class of gateways that store the content item and a rate of content requests that are forwarded to the content server or other class trackers, based on requests for the content item entering its class and the congestion signals received from other class trackers.

Abstract: The present invention concerns the replication of data, in particular the replication of data in a peer-to-peer network of mobile devices. Each device stores a plurality of data items. When two devices come into range, a decision as to whether to replicate a data item is made in dependence the extent to which that data item has been requested by other devices, and (b) the extent to which that data item is replicated on other devices. In this way, both the demand and supply of a data item are taken into account.

Abstract: A method and an apparatus for generating a privacy-preserving behavior predictor with incentive are provided, derived from verifiable and non-verifiable attributes from a plurality of agents. The privacy-preserving behavior predictor is based on regression (e.g., ridge-regression), is ?-differentially private and the incentive in the form of payments to each agent are ?-jointly differentially private. A method and an apparatus for generating a recommendation are also provided, derived from verifiable attributes from an agent and the ?-differentially private behavior predictor with incentive.

Abstract: A content distribution network, including: a content server that stores a set of content items; a plurality of gateways for storing and serving content requests to a subset of the content items, the plurality of gateways being grouped into a plurality of classes of gateways; and a plurality of class trackers corresponding to the plurality of classes; wherein each class tracker manages a placement of content items and an assignment of content requests for its class of gateways; wherein the plurality of class trackers exchange congestion signals among themselves; wherein, for each content item, each class tracker determines a fraction of gateways in its class of gateways that store the content item and a rate of content requests that are forwarded to the content server or other class trackers, based on requests for the content item entering its class and the congestion signals received from other class trackers.

Abstract: Finding the space spanned by user profiles of consumed items for making recommendations commences by first estimating a mean and covariance for a set of labeled items associated with a profile. Thereafter, a vector is identified that belongs to a convex cone spanned by the user profiles based on the estimated mean and covariance, the labels and items. The labels are mirrored in a negative space defined by the identified vector. The weighted covariance matrix is computed based on the mirrored labels; and eigenvalues and eigenvectors are computed of the weighted covariance matrix. A first set of eigenvalues share a value and wherein a remainder of the eigenvalues correspond to eigenvectors that span the profile.

Abstract: A method, apparatus and system for isolating microphone audio include recording audio using at least two microphones using a target microphone of the array of microphones, determining an attenuation factor for audio originating from respective locations of other microphones using a target microphone of the array of microphones, determining a delay factor for audio originating from respective locations of other microphones of the array of microphones, and implementing the determined attenuation factor and delay factor for removing audio originating from respective locations of the other microphones from an audio signal captured by the target microphone to isolate the audio signal captured by the target microphone. The method, apparatus and system further include processing the isolated audio signal of the target microphone to determine audio attributes of the isolated audio signal of the target microphone and determining using the audio attributes, respective sources of audio in the isolated audio signal.

Abstract: A method for recommending content items to a user is provided. It includes: (i) receiving one of at least an acceptance input and a rejection input from a user in relation to content presented to the user; (ii) in response to an acceptance input, rendering the presented content, or in response to a rejection input, selecting fresh content for presentation; and, (iii) repeating steps (i) and (ii) until a acceptance input is received. Content is selected in dependence on a associated probability associated with that content. The probability is increased in response to an acceptance input, the increase being determined in part on a measure of a predicted reduction in user satisfaction that would be associated with an additional rejection input.

Abstract: A method includes: receiving a first set of records, each record received from a respective user in a first set of users, and including a set of tokens and a set of items, and kept secret from parties other than the respective user, evaluating the first set of records by a recommender system using a first garbled circuit based on matrix factorization to obtain a masked item profile for each of a plurality of items in the first set of records, receiving a recommendation request from a requesting user for a particular item, and transferring the masked item profiles to the requesting user, wherein the requesting user evaluates a second record and the masked item profiles by using a second garbled circuit based on ridge regression to obtain the recommendation about the particular item and only known by the requesting user. An equivalent apparatus is configured to perform the method.

Abstract: A method includes: receiving a set of records from a source, wherein each record in the set of records includes a set of tokens, and wherein each record is kept secret from parties other than the source, and evaluating the set of records with a garbled circuit, wherein the output of the garbled circuit is a count based on the set of tokens. An apparatus includes: a processor, that communicates with at least one input/output interface and at least one memory in signal communication with the processor, and wherein the processor is configured to: receive a set of records from a source, wherein each record includes a set of tokens, and wherein each record is kept secret from parties other than the source and evaluate the set of records with a garbled circuit, wherein the output of the garbled circuit is a count based on the set of tokens.

Abstract: A method includes: receiving a set of records, wherein each record in the set of records is received from a respective user and includes a set of tokens and a set of items, and wherein each record is kept secret from parties other than the respective user, receiving a recommendation request from a requesting user for a particular item, evaluating the set of records by using a garbled circuit based on matrix factorization, wherein the output of the garbled circuit includes a masked item profile for a particular item and a masked user profile for the requesting user, receiving an encrypted user profile from the requesting user, generating an encrypted recommendation for the particular item based on the encrypted user profile, and providing the encrypted recommendation to the requesting user, wherein the requesting user decrypts it to obtain the recommendation. An equivalent apparatus is configured to perform the method.

Abstract: A method includes: receiving a set of records from a source, wherein each record in the set of records includes a set of tokens and a set of items, and wherein each record is kept secret from parties other than the source, receiving at least one separate item, and evaluating the set of records and the at least one separate item by using a garbled circuit based on matrix factorization, wherein the output of the garbled circuit includes an item profile for each at least one separate item. An apparatus includes: a processor that communicates with at least one input/output interface, and at least one memory in signal communication with the processor, wherein the processor is configured to perform the method.

Abstract: Methods and apparatus for a system providing group recommendations, event scheduling, and forming consensus agreements among a group of disparately located users are provided by the present principles. Communication among the disparately located users may be achieved through social media tools, online polling, chatting, and texting. The methods and apparatus allow a user profile to be constructed based on ratings that a user provides to items in a database. The items may comprise such things as restaurants, movie theaters, or other entertainment and group activities. The items may comprise feature vectors including attributes of the individual items. With user profiles constructed, the methods and apparatus may allow prediction of a rating that an individual with a particular user profile may give to a similar item in a database. The system may be used to predict the best choice for a group activity by considering the ratings of all users within a group.

Abstract: A method and apparatus for protecting user privacy in a recommender system are described including determining what information to release to a user for a movie, transmitting the information to the user, accepting obfuscated input from the user and estimating the user's non-private feature vector. Also described are a method and apparatus for protecting user privacy in a recommender system including receiving movie information, accepting a user's movie feedback, accepting user's private information, calculating an obfuscation value and transmitting the obfuscation value.

Abstract: A method is provided for performing a content search through comparisons, where a user is presented with two candidate objects and reveals which is closer to the user's intended target object. The disclosed principles provide active strategies for finding the user's target with few comparisons. The so-called rank-net strategy for noiseless user feedback is described. For target distributions with a bounded doubling constant, rank-net finds the target in a number of steps close to the entropy of the target distribution and hence of the optimum. The case of noisy user feedback is also considered. In that context a variant of rank-nets is also described, for which performance bounds within a slowly growing function (doubly logarithmic) of the optimum are found. Numerical evaluations on movie datasets show that rank-net matches the search efficiency of generalized binary search while incurring a smaller computational cost.

Abstract: In interactive content search through comparisons, a search for a target object in a database is performed by finding the object most similar to the target from a small list of objects. A new object list is then presented based on the earlier selections. This process is repeated until the target is included in the list presented, at which point the search terminates. A solution to the interactive content search problem is provided under the scenario of heterogeneous demand, where target objects are selected from a non-uniform probability distribution. It has been assumed that objects are embedded in a doubling metric space which is fully observable to the search algorithm. Based on these assumptions, an efficient comparison-based search method is provided whose cost in terms of the number of queries can be bounded by the doubling constant of the embedding c, and the entropy of demand distribution, H.

Abstract: A consumer electronic device hosts a media application that obtains media content use data for a user. The media application interfaces with a server that analyzes the media content use-related data based on a budget-constrained DCLEF and/or a distortion-constrained DCLEF mechanism. The user is then compensated for their disclosed use data based on the severity of the privacy incursion.