Emc Corporation

Amazon Technologies, Inc.

Eric Alfred Herrmann

Janet Lynn Schneider

Dianne C Thompson

Carolina P Uhlmann

Patrick M Simonich

Stephan G Betz

Nathan Kryger

Luke Aron Snyder

David Richard Brandt

Mu Chai

Joel Andrew Shapiro

Robert Lockhart Reid

John Todd Larason

David J Langrock

An external traffic advertisement system is provided that generates advertisement sets based on analysis of visits to a web site that were referred by an external source. The advertisement system aggregates the referral information for each referral type. A referral type may be defined by one or more of keyword text derived from the query text of the referrals, landing page type, external source, product identifier, and so on. The advertisement system may, for each referral type, aggregate the total revenue from the visits of that referral type and may generate a count of the number of converting visits for that referral type. The advertisement system then identifies those referral types whose aggregated information satisfies an advertisement criterion and generates an advertisement set for each identified referral type with a keyword derived from keyword text and with a link based on the landing page type of the referral type.

Advertisement generator based on external traffic

The accuracy of bid amounts for electronic advertising is improved by accounting for factors such as the cost-per-click (CPC) ratio for each ad. When a provider such as a search engine selects advertisements using automated auctions, it can be desirable for an advertiser to avoid underbidding for ads when the ads generate a significant amount of revenue or profit, or are otherwise performing well. Various algorithms can be used to generate a bid adjustment factor that allows bid values to be increased (or decreased) as appropriate, based on information such as CPC information. By calculating a separate adjustment factor, the amount of adjustment can be monitored and/or capped to avoid overspending. The algorithms also can utilize information at various levels of categorization, and at different time intervals, depending on the amount and type of information available, in order to provide an accurate and significant result.

Automatic bid adjustments for electronic advertising

Bid amounts for electronic advertising can be adjusted throughout the day, or for different days, according to a day parting schedule based on factors such as variations in efficiency. For any set of advertisements grouped based on factors such as keyword, landing page, geographic location, user demographic, etc., values can be forecast for each time period throughout the day. A variation threshold is used to group adjacent periods of time into partitions, and the threshold can be varied until the number of partitions meets the requirements of the provider with whom the advertisement is to be placed. An adjustment factor can be determined for each partition using the forecast information, and these factors can be uploaded to the provider to adjust the base bid price for any advertisement in that group at the appropriate times throughout the day.

Bid adjustment scheduling for electronic advertising

A method and system for augmenting keywords, submitted to advertisement placement services, that are not performing as expected is provided. An advertisement system analyzes the performance of keywords of advertisement sets submitted with advertisement placement services, such as search engine services. Based on the analysis, the advertisement system identifies keywords that are candidate keywords for augmentation. The advertisement system then identifies augmentation terms for the candidate keywords. The advertisement system then augments the candidate keyword of an advertisement set with the augmentation term and submits that augmented advertisement set with the augmented keyword to an advertisement placement service.

Augmenting advertisement keywords to increase conversion rate

Systems and methods for backing up data of a client. In a system that includes clients in communication with a server, the data of the client is backed up by first enumerating writers that are active on a client. Metadata from the active writers is received and identifies data to be backed up. A snapshot of the client is taken and the client data identified in the metadata received from the writers is backed up from the snapshot.

Systems and methods for backing up data

Systems and methods for backing up and/or restoring data. When a backup operation is initiated, systems and methods are provided for creating a single snapshot of the backup items, including backup groupings. The single snapshot is used by a backup/recovery application to perform a save process on each backup grouping. By using the same snapshot, the backup is performed based on the same point in time so that the backed up data across the client system is consistent and synchronized. When a recovery operation is initiated, recovery items (e.g., backup groupings, writers and writer components) are selected from backup grouping of the client.

Creation of a single snapshot using a server job request

Systems and methods for backing up and/or restoring data. When a backup operation is initiated, systems and methods are provided for creating a single snapshot of the backup items, including backup groupings. The single snapshot is used by a backup/recovery application to perform a save process on each backup grouping. By using the same snapshot, the backup is performed based on the same point in time so that the backed up data across the client system is consistent and synchronized. When a recovery operation is initiated, recovery items (e.g., backup groupings, writers and writer components) are selected from backup groupings of the client.

Creation of a single client snapshot using a client utility

Systems and methods for generating selection representations for items in a tree structure and applying selection representations to logical groupings. An exemplary method includes retrieving a first tree structure that reflects a hierarchy of data from at least one of memory or storage, identifying a first grouping of items in the first tree structure, identifying a remainder of items in the first tree structure, displaying the first grouping and the remainder of items in the first tree structure on the display, receiving positive selections or unselections of at least one of the first grouping of items or the remainder of items for including or excluding in performing a predetermined function on the positively selected or unselected items, generating a selection representation for the first grouping of items and the remainder of items based on the user input, and merging the selection representation for the first grouping of items and the remainder of items to generate a final selection representation.

Selection representation methods applied to logical groupings

Backup and restore operations using a single snapshot driven by a server job request

Backup and restore operations using a single snapshot

Systems and methods for backing up or restoring interdependent applications. During a backup or recovery process, the writers and writer components included in the backup groupings of a client are displayed. Some of the writers and writer components can be individually selected for backup or recovery. Some of the writer components may have a dependency on a writer component in another writer. The dependency is automatically selected, although a user can disable the automatic selection of the dependency or deselect the dependency. The dependency is then backed up or recovered along with the selected writers and selected writer components.

Backup and restore operations of interdependent system components

Systems and methods for recovering data from a backup copy and for backing up data. When a recovery operation is initiated, recovery items are selected from backup groupings of the client. The recovery items can include backup groupings, writers, and writer components. After the recovery items are selected, backed up metadata for each selected writer is retrieved from the backed up data. The backed up metadata is then queried to identify the restore method of the writer. The data of the client is then recovered by implementing the restore method included in the backed up metadata of the writer. During a backup operation, some of the backup groupings, as well as the content of the backup groupings, can be individually selected for backup. In both backup and recovery, a visual indication may be provided to identify individual selectability.

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Snohomish, WA, United States of America

Eric Alfred Herrmann