Abstract: Various embodiments of a system and method for generating recommendations based on similarities between location information of multiple users are described. Various embodiments may include a location-based recommendation system configured to, for each given user of a group of users, determine the given user has traveled to one or more respective locations and determine one or more characteristics of the given user. The system may also determine that a particular user has traveled to or will travel to each of one or more particular locations. The system may further determine a similarity between the one or more particular locations and one or more locations to which specific ones of the group of users have traveled. The system may generate a recommendation for the particular user based on at least some of the determined characteristics of the specific ones of the group of users for which the similarity was determined.

Abstract: Content items, such as e-books, audio files, video files, etc., may be recommended to a user based on the user's presence at a geolocation or venue. Geolocation is the geospatial location of the user, while a venue is a designated area for an activity, such as a concert hall, aircraft, waiting room, etc. The recommendations may be of content items relating to the geolocation or venue, or they may be content items being accessed by others who are, or have been, in approximately the same geolocation or venue.

Abstract: Disclosed are various embodiments for determining the effects of modifying a network page based at least upon the implicit behaviors of users. An executable network page is generated to record the implicit behaviors of users. A position density map is then generated from the recorded implicit behavior to identify the content on the network page that has a high or low level of user interaction. The position density map is then analyzed to determine if the content on the network page needs to be revised. Subsequent A/B tests relating to revisions made to the network page may be run to ascertain the effect of changing the network page using the position density map.

Abstract: User content access events pertaining to a content item, such as an e-book, audio, video file, and so on, are collected and analyzed to determine progress data, including abandonment information about when the content item, or a portion thereof, has been abandoned. Once determined, recommendations may be presented based on progress data from similar users.

Abstract: User content access events pertaining to a content item, such as an ebook, audio, video file, and so on, are collected and analyzed to determine progress data, including abandonment information about when the content item, or a portion thereof, has been abandoned. Once determined, recommendations may be presented based on the progress data from similar users.

Abstract: Content items, such as e-books, audio files, video files, etc., may be recommended to a user based on the user's presence at a geolocation or venue. Geolocation is the geospatial location of the user, while a venue is a designated area for an activity, such as a concert hall, aircraft, waiting room, etc. The recommendations may be of content items relating to the geolocation or venue, or they may be content items being accessed by others who are, or have been, in approximately the same geolocation or venue.

Abstract: Content items, such as e-books, audio files, video files, etc., may be recommended to a user based on the user's presence at a geolocation or venue. Geolocation is the geospatial location of the user, while a venue is a designated area for an activity, such as a concert hall, aircraft, waiting room, etc. The recommendations may be of content items relating to the geolocation or venue, or they may be content items being accessed by others who are, or have been, in approximately the same geolocation or venue.

Abstract: A personalization network service enables developers to develop recommenders that can be made available to content site operators for providing recommendations to end users. The personalization network service may also be capable of optimizing the use and selection of the recommenders for different end users, groups or segments of end users, content sites, and the like.

Abstract: Content items, such as e-books, audio files, video files, etc., may be recommended to a user based on the user's presence at a geolocation or venue. Geolocation is the geospatial location of the user, while a venue is a designated area for an activity, such as a concert hall, aircraft, waiting room, etc. The recommendations may be of content items relating to the geolocation or venue, or they may be content items being accessed by others who are, or have been, in approximately the same geolocation or venue.

Abstract: A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user. Advantageously, the web sites need not host the infrastructure for providing such content.

Abstract: A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user. Advantageously, the web sites need not host the infrastructure for providing such content.

Abstract: A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user. Advantageously, the web sites need not host the infrastructure for providing such content.

Abstract: A personalization network service enables developers to develop recommenders that can be made available to content site operators for providing recommendations to end users. The personalization network service may also be capable of optimizing the use and selection of the recommenders for different end users, groups or segments of end users, content sites, and the like.

Abstract: A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user.

Abstract: A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user. Advantageously, the web sites need not host the infrastructure for providing such content.

Abstract: A personalization network service enables developers to develop recommenders that can be made available to content site operators for providing recommendations to end users. The personalization network service may also be capable of optimizing the use and selection of the recommenders for different end users, groups or segments of end users, content sites, and the like.

Abstract: A personalization network service enables developers to develop recommenders that can be made available to content site operators for providing recommendations to end users. The personalization network service may also be capable of optimizing the use and selection of the recommenders for different end users, groups or segments of end users, content sites, and the like.

Abstract: A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user. Advantageously, the web sites need not host the infrastructure for providing such content.

Abstract: A service is disclosed for enabling web sites and other entities to provide item recommendations and other behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations between particular items, and stores resulting datasets that map items to associated items. The web service's interface also provides various API calls for enabling the web sites to request item recommendations and other behavior-based content, including but not limited to personalized recommendations that are based on the event history of the target user.

Abstract: A service is disclosed for enabling web sites and other entities to provide behavior-based content to end users. The service can be implemented as a web service that is remotely accessible over the Internet. Web sites use the web service's interface to report events descriptive of item-related actions performed by end users (e.g., item views, item purchases, searches for items, etc.). The web service analyzes the reported event data on an aggregated basis to detect various types of associations, including associations between particular search queries and items. The detected associations are recorded in site-specific datasets, and are made available to the corresponding sites via the service's interface.