Symantec Corporation

Adobe, Inc.

Symantec Operating Corporation

Veritas Technologies LLC

Russell Robert Stringham

Sachin Soni

Anmol Dhawan

Ashish Duggal

Kevin Gary Smith

Ynn-Pyng Tsaur

Suren Sethumadhavan

Viswanathan Swaminathan

Ryan A Rossi

Eunyee Koh

Anup Bandigadi Rao

Sungchul Kim

Walter Wei-Tuh Chang

Aditya Anil Gokhale

Jonathan Ludwig

Dale Cardin

Carl J Appellof

Eduardo Suarez

Aswad Shrikrishna Kulkarni

Jason Ivey

Erik Prusse

Paul Madden

Techniques and systems are described for analytics system entity resolution. Typed higher-order node combinations are determined within a dataset, and an amount of similarity between two arbitrary nodes within the dataset is determined based on the typed higher-order node combinations. The amount of similarity enables the digital analytics to accurately perform source resolution of portions of the dataset to a respective source, and may be utilized to control output of digital content to a client device.

Analytics system entity resolution

Offline consumer behavior and interactions are observed using beacons positioned at venues where consumers spend time and interact with each other. The beacons communicate with mobile computing devices that are carried by the observed consumers. The observed consumer behavior provides actionable insights into how consumers influence each other. For example, the people that a particular consumer spends time with form a 'circle of influence' associated with that consumer. If the consumer makes a purchase, members of the circle of influence are observed to understand the degree to which they were influenced by the purchase, if at all. Metrics that quantify a consumer's influence over other consumers allow marketers to more effectively target both the influencing and influenced consumers. Also, if relatively little information is known about a particular consumer, that consumer's digital marketing profile can be supplemented using information known about the consumers with whom he/she often spends time.

Consumer influence analytics with consumer profile enhancement

Systems and methods are disclosed herein for attributing credit to online consumer touchpoints for a consumer performing an action. The systems and methods involve determining whether a consumer is in a particular environment for an online consumer touchpoint by detecting an external viewing condition for the consumer for the online consumer touchpoint. The systems and methods determine that the consumer performed an action, such as a conversion, following the online consumer touchpoint and additional online consumer touchpoints. An effectiveness of the online consumer touchpoint in the particular environment is determined and used to attribute relative credit to the online consumer touchpoint and the additional online consumer touchpoints for the consumer performing the action.

Attribution that accounts for external viewing conditions

Gauging consumer interest of in-person visitors is described. In one or more embodiments, a promotional apparatus having a display screen and a wireless beacon is deployed at a venue. The promotional apparatus presents a video having multiple video segments. During the presentation, the beacon and a mobile device of a venue visitor communicate wirelessly to determine a proximity of the visitor to the display screen. Multiple distances are determined at multiple times. A path of movement can be determined from the distances over time. If the visitor alters a direction of travel to veer toward the screen or stops walking close to the screen, a system infers that the video has engaged the visitor's attention. By linking particular video segments to times at which the mobile device is proximate to the display screen, the system can further infer consumer interest in specific product features being shown at those times.

Gauging consumer interest of in-person visitors

Disclosed systems and methods store interaction data by user and date. A computing device receives a unique visitor interaction data representing a first interaction between an entity and a visitor. The computing device accesses a list of file set identifiers. Each file set identifier corresponds to a respective set of users grouped together into a file set. The computing device computes a target file set identifier and matches the target file set identifier to a file set identifier from the list that identifies a file set that stores user interaction data for the entity. The computing device routes the first visitor interaction data to the identified file set. The computing device stores the first visitor interaction data and the second visitor interaction data sorted according to the first timestamp and the second timestamp.

Facilitating queries for interaction data with visitor-indexed data objects

A multi-cluster database management system is disclosed that distributes and manages data across a multi-cluster database through the use of cluster partitions. The multi-cluster database management system assigns cluster partitions to clusters of the multi-cluster database. The multi-cluster database management system can evenly or substantially evenly divide the cluster partitions and associated data among the clusters of the multi-cluster database. The multi-cluster database management system can scale in or out by adding or removing clusters from the multi-cluster database when needed or desired. Once a cluster is added or removed, the multi-cluster database management system re-balances the cluster partitions and the associated data across the clusters of the modified multi-cluster database.

Processing data in a distributed database across a plurality of clusters

A digital medium environment is described to determine textual content that is responsible for causing a viewing spike within a video. Video analytics data associated with a video is queried. The video analytics data identifies a number of previous user viewings at various locations within the video. A viewing spike within the video is detected using the video analytics data. The viewing spike corresponds to an increase in the number of previous user viewings of the video that begins at a particular location within the video. Then, text of one or more video sources or video referral sources read by users prior to viewing the video from the particular location within the video is analyzed to identify textual content that is at least partially responsible for causing the viewing spike.

Determining textual content that is responsible for causing a viewing spike within a video in a digital medium environment

Techniques are provided for transforming information about unique visits to a website or interactions with a mobile application by a single individual on different devices into unified analytical data representing these visits. One or more visitor stitching models can be used to quantify unique visits as belonging to the same person with a certain level of confidence. In addition to maintaining separate records for each unique visit, a unified record is generated, which represents a combination of the unique visits by the same person. Various analytics can then be performed on the unique and unified records. The unified records are favored over the separate data records wherever the stitching model corresponding to the unified record provides a certainty that meets or exceeds a user-specified confidence level. The visitor stitching model used for the analytics is considered non-committal because different models can be employed or none at all, depending on user preferences.

Non-committal visitor stitching

Managing a distributed database across a plurality of clusters

A method and apparatus for optimizing a backup chain using synthetic backups is described. In one embodiment, a method for creating synthetic incremental backups to optimize a backup chain comprises accessing a backup chain, which further comprises a plurality of incremental backups and determining schedule information defining a number of incremental backups to use to create one or more synthetic incremental backups representing the plurality of incremental backups from the backup chain, wherein the number of backups is defined by a numerical progression.

Method and apparatus for optimizing a backup chain using synthetic backups

A method, system, and computer-readable storage medium for managing backup operations of virtual machines are provided. According to one embodiment, a backup application initiates a snapshot of a storage volume, which stores a collection of virtual hard disk drives. A collection of virtual machines access the collection of virtual hard disk drives. The backup application accesses a collection of lists of changes to data. The collection of lists and the data are stored in the collection of virtual hard disk drives. A first list among the collection of lists is generated by a first virtual machine. The changes to data are made by the collection of virtual machines. The backup application generates an incremental backup of the first virtual hard disk drive by copying data from the snapshot in response to the first list identifying that the data changed subsequent to the generation of the prior backup.

System and method for managing backup operations of virtual machines

Techniques for providing incremental backup restoration are disclosed. In one particular exemplary embodiment, the techniques may be realized as a computer implemented method for providing incremental backup restoration comprising setting one or more allocated electronic storage indicators each indicating an allocated portion of electronic storage, comparing the one or more allocated electronic storage indicators with one or more prior backups in reverse chronological order starting from a most recent backup and proceeding until all of the one or more allocated electronic storage indicators have been identified in the one or more prior backups, and restoring the one or more prior backups corresponding to the one or more allocated electronic storage indicators.

Techniques for providing incremental backups

A method and apparatus for performing file-level restoration from a block-based backup file stored on a sequential storage device is described. In one embodiment, a method of processing a backup file to perform file-level restoration from a sequential storage device comprises generating extent information, wherein the extent information pertains to at least one file system object associated with a backup file, wherein the backup file is to be stored on a sequential storage device, wherein the backup file is block-based and processing a backup catalog, wherein the backup catalog indicates locations of various portions of the extent information and is used to restore a file system object.

Method and apparatus for performing file-level restoration from a block-based backup file stored on a sequential storage device

A computer-implemented method may create a first full backup of a set of data units at a first point in time. The method may create, at a second point in time, a representation of one or more data units in the set of data units that have been modified since the first point in time. The method may determine, based at least in part on the representation of one or more data units that have been modified since the first point in time, a difference between a state of the set of data units at the first point in time and a state of the set of data units at the second point in time. The method may use the difference to update the first full backup to a second full backup that comprises modifications made to the set of data units between the first and second points in time.

Growing community of inventors

Orem, UT, United States of America

Russell Robert Stringham