International Business Machines Corporation

Amazon Technologies, Inc.

Maplebear Inc.

Rahul Urgaonkar

Dinesh C Verma

Theodoros Salonidis

Swati Rallapalli

Bong Jun Ko

Jorge J Ortiz

Xiping Wang

Keith William Grueneberg

Supriyo Chakraborty

Nirmit V Desai

Christian Makaya

Bongjun Ko

Satheesh Ramalingam

Amarsingh Buckthasingh Winston

Mohan Padmanabhan

Manish Rao

Adhvik Arun Shetty

Moping Dou

Hargun Kaur

Martin G Kienzle

Shahrokh Daijavad

A method for targeted advertisement includes transmitting a pre-filter to the user device, responsive to contextual information from a user device, to determine, using a processor, one or more inferences based on physical browsing information, collected at the user device, in compliance with one or more privacy policies of the user. The method also includes receiving one or more inferences determined by the pre-filter from the user device and transmitting one or more targeted advertisements to the user device based on one or more inferences.

Recommendations based on private data using a dynamically deployed pre-filter

Methods and systems for execution of distributed analytics include building a global linked structure that describes correspondences between dataset metadata structures, analytics metadata structures, and location metadata structures and that encodes compatibility between respective datasets, analytics, and locations. A set of analytics and compatible datasets for execution is determined based on the dataset metadata structures, analytics metadata structures, and global linked structure. An optimal execution location is determined based on the determined set of analytics and compatible datasets, the location metadata structures, and the global linked structure. The set of analytics and compatible datasets are deployed to the optimal location for execution.

Linking, deploying, and executing distributed analytics with distributed datasets

A data mining method, system, and non-transitory computer readable medium include obtaining a subset of public records of data in a public domain and performing data mining, via private domain data, within the subset of the public records of data to find data in the public domain corresponding to a particular individual.

System, method, and recording medium for data mining between private and public domains

Methods are provided. A method includes announcing to a network meta information describing each of a plurality of distributed data sources. The method further includes propagating the meta information amongst routing elements in the network. The method also includes inserting into the network a description of distributed datasets that match a set of requirements of the analytics task. The method additionally includes delivering, by the routing elements, a copy of the analytics task to locations of respective ones of the plurality of distributed data sources that include the distributed datasets that match the set of requirements of the analytics task.

Content-based distribution and execution of analytics applications on distributed datasets

A data mining method, system, and non-transitory computer readable medium, include defining a set of filter constraints as a filter function for clustering users' private records of data of a private domain, selecting a subset of users' public records of data from a filtered set of data from a public domain that is common with the users' private records of data, and creating a data file including the matched user of the private domain to the public records of the user of the private domain, where the set of the filter constraints comprises a function that captures the subset of the users' public records of data who are of interest to the private domain, and only performs data mining with that set of information from the public domain.

Systems, methods, and computer-readable media are disclosed for optimizing network performance on a computer device to improve quality of experience by determining which network settings on the computing device to adjust. A clustering algorithm may identify various classes of networks and a classification algorithm may determine a network class specific to a network on a computing device. The effects of certain network settings for that networks class may be determined and the network setting and/or settings that optimizes the network performance may be promoted. The system may periodically analyze network data to recalculate the appropriate networks class and may determine different network settings based on the recalculation, facilitating mid-session improvements to the quality of experience.

Machine learning-based playback optimization using network-wide heuristics

Systems and methods for optimizing network settings

Systems, methods, and computer storage media are described herein for optimizing adaptive bitrate streaming for content (e.g., streams of live events). Bitrate selections may be made based at least in part on the current state of the playback. When the playback is in a transient state (e.g., when the user has recently played or navigated within the content), bitrate selections may be determined utilizing a virtual buffer that simulates a playback buffer. The virtual buffer may be initialized with a predetermined fullness value. As content fragments are received and queued on the playback buffer, the fullness values for the virtual buffer and the playback buffer may be adjusted differently. When the fullness of the playback buffer exceeds the virtual buffer, subsequent bitrate selections may be determined utilizing the playback buffer. The virtual buffer may be utilized to simulate a steady state playback buffer while the playback buffer populates.

Techniques for short buffer adaptive bitrate streaming

Methods and systems for targeted advertisement include transmitting a pre-filter to a user device, responsive to contextual information supplied by the user device to determine one or more inferences based on physical browsing information, collected at the user device, in compliance with one or more privacy policies of the user. One or more targeted advertisements are determined, using a processor, based on the one or more inferences. The one or more targeted advertisements are transmitted to the user device.

Technical solutions are described for selecting components from multiple vendors for a system. An example computer-implemented method includes receiving, by a processor, an environment map that identifies a first component placeholder of the system. The computer-implemented method further includes identifying, by the processor, that the first component placeholder interfaces with a second component placeholder of the system. The computer-implemented method further includes determining, by the processor, a role assigned to the first component placeholder, where the role indicates a type of data that a first component at the first component placeholder communicates with a second component at the second component placeholder. The computer-implemented method further includes determining, by the processor, a list of components for selecting the first component, where each component from the list of components matches the role assigned to the first component placeholder.

Industrial setup composition

A data mining method, system, and non-transitory computer readable medium, include defining a set of filter constraints as a filter function for clustering users' private records of data of a private domain, obtaining a set of data from a public domain by applying the filter function to users' public records of data of the public domain, selecting a subset of the users' public records of data that is common with the users' private records of data, and performing data mining on the selected subset of the users' public records of data in combination with the users' private records of data to match a user of the private domain to public records of the user of the private domain.

Growing community of inventors

Rye, NY, United States of America

Rahul Urgaonkar