A9.com, Inc.

Amazon Technologies, Inc.

Jiong Wang

Christopher Laurence Scofield

Elmore Eugene Pope

Brad Eugene Marshall

Jonathan A Gold

Colin M Saunders

A method for generating search results based on a search term and displaying the search results in one or more groupings. The method includes receiving a search term entered by a user, selecting one or more search result groupings based on the search term entered by the user and at least in part on a bid amount associated with the search term, providing search results based on the search term entered by the user for each search result grouping, and displaying the search groupings to the user.

System and method for displaying columns of search results

A method and system for assisting a user to generate a task list based on a task description is presented. The task description can be provided as user input or detected based on information about the user. The generated task list includes a series of actions (subtasks) which as a whole complete a task specified in the task description and relevant information. During the task list being generated, some actions are automatically executed without user intervention, or remembered for future execution.

Managing task lists utilizing integrated information requests

Users who visit a network site typically visit other sites in the same session. The surfing pattern or 'trail' through the pages may be significant once aggregated, because it outlines the underlining relationship between those pages or sites. Once such user navigational trail data is available, the relationship between network sites on such user trails may used to make various decisions regarding advertising and keyword management. Additionally, the relative popularity of each trail may be used to rank or compute relative weights for the various user trails. Such information may then aid in keyword suggestion and advertising decisions.

Method and system for keyword selection based on proximity in network trails

Users that visit a network site typically visit other sites in the same session. The surfing pattern or 'trail' through the sites is significant because it may outline the underlining relationship between those sites. Once such data is available, the relationship between sites on the same user trails may be used to determine the placement of advertisements for sites by publishers. Additionally, the popularity or volume of traffic that navigates along a particular user trail may be used to affect the ranking/ordering of advertisements placed on a certain publisher site. An advertising broker may determine advertising pricing in part based on navigational path or user trail information. Thus, placing advertising on sites that are closer in proximity to the advertised site may cost more than placing advertising on sites not as close in proximity to the advertised site.

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Union City, CA, United States of America

Jiong Wang