Patent application number | Description | Published |
20080228469 | ROLLUP FUNCTIONS FOR EFFICIENT STORAGE, PRESENTATION, AND ANALYSIS OF DATA - Methods of organizing a series of sibling data entities in a digital computer are provided for preserving sibling ranking information associated with the sibling data entities and for attaching the sibling ranking information to a joint parent of the sibling data entities to facilitate on-demand generation of ranked parent candidates. A rollup function of the present invention builds a rollup matrix ( | 09-18-2008 |
20080243631 | SERVICES FOR PROVIDING ITEM ASSOCIATION DATA - 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. | 10-02-2008 |
20080243632 | SERVICE FOR PROVIDING ITEM RECOMMENDATIONS - 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. | 10-02-2008 |
20080250026 | RECOMMENDATIONS BASED ON CROSS-SITE BROWSING ACTIVITIES OF USERS - A system provides recommendations of web sites, web pages, and/or products to a user based on web pages viewed during a current browsing session. In one embodiment, a browser plug-in or other client program monitors and reports information regarding browsing activities of users across multiple web sites. The resulting cross-site browse histories of the users are analyzed on an aggregated basis to detect behavior-based associations between particular sites, pages and/or products. The detected associations are in turn used to provide personalized recommendations to users. The associations and recommendations may also be based on an automated analysis of the content of the web pages represented in the users' browse histories. | 10-09-2008 |
20100049663 | SERVICE FOR PROVIDING ITEM RECOMMENDATIONS - 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. | 02-25-2010 |
20110238525 | DISCOVERY OF BEHAVIOR-BASED ITEM RELATIONSHIPS - Various processes are disclosed for discovering item relationships between particular items, such as products represented in an electronic catalog, based on monitored user behaviors (e.g., item viewing activities, item purchases, shopping cart activities, etc.). The discovered item relationships may, for example, be used to generate personalized item recommendations for users, and/or to supplement item detail pages of an electronic catalog with lists of related items. Also disclosed are processes for generating personalized item recommendations based on users' search activities and browse node visits. | 09-29-2011 |
20110258085 | SERVICES FOR PROVIDING ITEM ASSOCIATION DATA - 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. | 10-20-2011 |
20120078747 | RECOMMENDATION SYSTEM CAPABLE OF ADAPTING TO USER FEEDBACK - A recommendation system uses feedback from users on specific item recommendations to assess the quality of the recommendation rules used to generate such recommendations. The feedback may be explicit (e.g., a user rates a particular recommended item), implicit (e.g., a user purchases a recommended item), or both. The system may use these assessments to modify the degree to which particular recommendation rules are used to generate recommendations. For instance, if a particular recommendation rule leads to negative feedback relatively frequently, the system reduce or terminate its reliance on the rule. In some embodiments, the system may also increase its reliance on recommendation rules that tend to produce positive feedback. | 03-29-2012 |
20120158552 | BEHAVIORAL DATA MINING PROCESSES FOR GENERATING PAIRWISE ITEM COMPARISONS - Data mining systems and methods are disclosed for generating data that is helpful to users in selecting between items represented in an electronic data repository, such as an electronic catalog. One disclosed data mining method generates pairwise comparison data for particular pairs of items. The pairwise comparison data for a given item pair reveals a tendency of users who consider both items in the pair to select one item over the other. The pairwise comparison data may be appropriately exposed to users of the electronic repository. For instance, an item detail page for item A may be supplemented with an indication that users who view both item A and item B select item B a specified percentage of the time. Another data mining method uses item viewing histories and item purchase histories of users in combination to identify pairs of items that are good candidates for being recommended in combination. | 06-21-2012 |
20120259729 | DISCOVERY OF BEHAVIOR-BASED ITEM RELATIONSHIPS - Various processes are disclosed for discovering item relationships between particular items, such as products represented in an electronic catalog, based on monitored user behaviors (e.g., item viewing activities, item purchases, shopping cart activities, etc.). The discovered item relationships may, for example, be used to generate personalized item recommendations for users, and/or to supplement item detail pages of an electronic catalog with lists of related items. Also disclosed are processes for generating personalized item recommendations based on users' search activities and browse node visits. | 10-11-2012 |
20130144684 | IDENTIFYING AND EXPOSING ITEM PURCHASE TENDENCIES OF USERS THAT BROWSE PARTICULAR ITEMS - A data mining system generates data values reflecting purchase tendencies of users who browse particular items in an electronic catalog. The data values may include conditional probability values representing, for example, a probability that, if a user makes a purchase after browsing a first particular item, the user will purchase a second particular item. The data values may be used to provide notifications on product pages of an electronic catalog. For example, an item detail page for a first item may be supplemented with a notification of one or more other items that tend to be purchased by those who browse the first item. | 06-06-2013 |