Amazon Technologies, Inc.

A9.com, Inc.

Battelle Memorial Institute

Jeremy Charles York

Russell Dicker

Robert G Cottrell

Jeffrey P Bezos

Brent Russell Smith

Ryan Justin Snodgrass

Joanna L Power

Matthew James Round

Andrej Gregov

Greg Linden

Josh Petersen

James J Thomas

Ron Kohavi

Kelly A Pennock

James A Wise

Anne Schur

David B Lantrip

Marc C Pottier

A subset of a set of components is selected for inclusion on a dynamically-generated page within a particular user context. The subset of components is selected based on scores associated with the components in the set. The score of a component is preferably determined based on measurements of user activity resulting from exposures of the components to users in the particular context.

Adaptive learning methods for selecting page components to include on dynamically generated pages

A subset of a set of components is selected for inclusion on a dynamically-generated web page within a particular user context. Each component may, for example, contain content generated by a respective code module or service. The subset of components is selected based on scores associated with the components in the set. The score of a component is preferably determined based on measurements of user activity resulting from exposures of the components to users in the particular context.

A subset of a set of components is selected for inclusion on a dynamically-generated web page within a particular user context. Each component may, for example, contain content generated by a respective code module or service. The subset of components is selected based on scores associated with the components in the set. The score of a component is preferably determined based on measurements of desired user activity resulting from exposures of the components to users in the particular context, and reflects a likelihood that other users within the same context will perform a desired action. The disclosed methods may also be used to select items, such as products, to suggest to users within specific contexts.

Adaptive learning methods for selecting web page components for inclusion in web pages

An interactive system enables users to generate and submit lists of items (e.g., products selected from an electronic catalog) for viewing by other users. The user-generated lists are selectively suggested to users of the system based (or based in part) on ratings of the user-generated lists. These ratings may, for example, be based on explicit ratings of the lists by users, and/or measures of how effective the respective lists are at driving purchases of items. In some contexts, the system may select one or more user-generated lists to present to a user based on a set of items purchased, viewed, or otherwise selected by the user, or based on the results of a search query submitted by the user.

Service for accepting and selectively exposing user-generated lists

An interactive system enables users to generate and submit lists of items (e.g., products) for viewing by other users. The user-generated lists are selectively suggested to users of the system based on their respective behaviors, such as their item viewing activities, searches, and/or item purchases. The system may monitor the behaviors of users who access particular user-generated lists, and based on the monitored behaviors, generate measures of the effectiveness of particular lists (e.g., effectiveness at driving item purchases). The measures of effectiveness may be considered in selecting particular lists to suggest.

A continuous website trial allows ongoing observation of user interactions with website for an indefinite period of time that is not ascertainable at initiation of the trial. Users are randomly assigned to either a control group or one or more test groups. The control and test groups are served different sets of web pages, even though they access the same website. During the trial, the web pages for the control group are held constant over time, while the web pages for the test group(s) undergo multiple modifications at separate occasions over time. As the web pages for the test group(s) are modified, statistical data collection continues to learn how user behavior changes as a result of the modifications. The statistical data obtained from the users of the various groups may be compared and contrasted and used to gain a better understanding of customer experience with the website.

Continuous usability trial for a website

Information retrieval systems and methods are disclosed for presenting items of interest to a user of a computer-based data repository, where the items are presented in the form of lists generated by other users. Users of a data repository may generate lists of items from the repository that are accessible by other users. In various embodiments, users generating lists may add supplemental commentary about the items and other personalizing information. The information retrieval systems and methods store the user-generated lists for future presentation to other users. When a user of the data repository submits a search query, items returned in the query's results are interpreted to be items of interest to the user, and in response, one or more lists determined to be similar to the items of interest are presented to the user.

Service for accepting and selectively exposing user-created lists of items

Information retrieval systems and methods are disclosed for presenting items of interest to a user of a computer-based data repository, where the items are presented in the form of lists generated by other users. Users of a data repository may generate lists of items from the repository that are accessible by other users. In various embodiments, users generating lists may add supplemental commentary about the items and other personalizing information. The information retrieval systems and methods store the user-generated lists for future presentation to other users. The online activities of a user of the data repository are monitored, and, in response to the user indicating an interest in an item, one or more lists determined to be similar to the indicated item are presented to the user.

Information retrieval systems and methods that use user-defined lists to identify related offerings

Computer processes are disclosed for automatically refining the order and/or content of context-specific lists of items (e.g., products) based on monitored actions of users. One such process involves outputting context-specific lists of items to users together with selectable controls for initiating displays of similar items. When users opt to view similar items, the users' actions performed in connection with the similar items are recorded. If the resulting level of user activity recorded for a particular similar item is sufficiently high, the item is automatically added to the associated context-specific list.

Automated discovery of items associated with a context based on monitored actions of users

A facility for presenting information about new items, such as new items available via a web site is described. The facility receives a request for information submitted on behalf of an identified user. In processing the request, the facility accesses a set of items having effective times. The facility performs a first filtering process to eliminate items of the set whose effective times indicate that the items are not new. The facility performs a second filtering process to eliminate items of the set in which the user likely has a low level of interest. Subsequent to both the first and second filterings, the facility presents to the user information about each of at least a portion of the filtered items.

Personalized promotion of new content

Systems and methods that use search queries to identify related lists

A computer-implemented system and method are disclosed that are capable of refining the order and/or content of a list of items. In one embodiment, user activity associated with each item displayed to users in a given context is monitored, and is used together with item exposure data to generate context-specific item weights. The weights for the same item in different contexts may be different. The selection of items included in a list presented to users, and/or the order in which the items in the list are displayed, may be adjusted over time based upon the relative weights associated with the items.

Computer processes for adaptively selecting and/or ranking items for display in particular contexts

A method for spatializing text content for enhanced visual browsing and analysis. The invention is applied to large text document corpora such as digital libraries, regulations and procedures, archived reports, and the like. The text content from these sources may be transformed to a spatial representation that preserves informational characteristics from the documents. The three-dimensional representation may then be visually browsed and analyzed in ways that avoid language processing and that reduce the analysts' effort.

Three-dimensional display of document set

The invention comprises a computer-implemented system and method for refining the order and/or content of a list of items. In one embodiment, the amount of user activity associated with each item displayed to users in a given context is monitored, used is to generate context-specific item weights. The weights for the same item in different contexts may be different. The selection of items included in a list presented to users, as well as the order in which the items in the list are displayed, may be adjusted over time based upon the relative weights associated with the items. This allows the items generating the greatest user interest in a particular context to be presented to first, or otherwise emphasized.

Growing community of inventors

Bothell, WA, United States of America

Jeremy Charles York