Amazon Technologies, Inc.

Google Inc.

Other

Scott Allen Mongrain

James G Robinson

Amy Lynn Sims

Kate Schutzengel

Antoine Sevilla

Takafumi Iwai

David Christopher Everly

Russell Dicker

Thomas Lowell Keller

Waqas Syed Ahmed

Logan Luyet Dillard

Nigel J Green

Terrence R Nightingale

Florin V Manolache

Aaron D Wilson

Corneliu Gabriel Alexandru Rudeanu

Val Dan Dar Ion I Rosca

Eric B Fox

David M Lifson

Sean William Blakey

Ian A McAllister

Valentin Radu Munteanu

Terrance R Nightingale

Alexander J Cox

Clayton A Williams

Eric F Gilmour

Teresa E Batten

Oystein Hernes

Sunil Ramesh

Joseph Spencer King

Elmore Eugene Pope

Srikanth Thirumalai

Bailiang Zhou

Jason P Patrikios

Joseph Xavier

Rahul H Bhagat

Grant Michael Emery

Whitney Gale Spathelf

Adam Callahan Sanders

Cyrus Khoshnevisan

Kemal Oral Cansizlar

Brian Cameros

Gregory J Meyers

Peng Shao

Benjamin Thomas Cohen

Jim Robinson

Terry Nightingale

Minal Mehta

Michael David Quinn

Eli Glen Rosofsky

Yongwen Liang

Carl K Lim

William W Gronim

Waquas Ahmed

Display screen or portion thereof with graphical user interface

Display screen or portion thereof with transitional graphical user interface

A digital map is displayed via a user interface in a map viewport. The digital map includes various features representing respective entities in a geographic area, each of the features being displayed at a same level of magnification. Geolocated points of interest are determined within the geographic area, and a focal point of the map viewport is determined. For each of indicators, the size of the indicator is varied in accordance with the distance between the geographic location corresponding to the indicator and the geographic location corresponding to the focal point of the map viewport. The indicators then are displayed on the digital map.

Dynamically varying visual properties of indicators on a digital map

Techniques for generating representative images are disclosed herein. In particular, various embodiments utilize an image generation service to generate representative images for categories and sub-categories of objects. Each representative image can be a stylized depiction of an aggregated image corresponding to a particular category of objects. A user can refine the search, or continue to browse, by selecting one of the representative images. This enables users to quickly identify features the user is looking for or would like to exclude, by depicting the sort of objects associated with that category.

Techniques for generating representative images

Disclosed are various embodiments for recommending a list of digital media to a user based upon digital media that the user is currently consuming. The list of recommendations is generated from an analysis of the digital media. Subsequently, the list of recommendations is stored on the user's device, and the user is alerted to the list's existence through the rendering of a notification on the user's display. Upon selection of an item from the list of recommendations, the selected digital media is rendered on the display of the user's device within the context of the user's application.

Digital media relationship analyzer and recommender

Disclosed are various embodiments for defining subcategories of items to be used in merchandising. The subcategories may be defined on the basis of item data and/or sales data for the items. Based on a distribution of the items in accordance with one or more of the item and/or sales data, implicit groups or subcategories can be identified and selected for merchandising purposes.

Automatic product groupings for merchandising

A computing system for searching for and identifying data repository deficits includes an interactive database of items, a data repository that stores a first type of information related to items, a search engine configured to identify items that do not have an amount of the first type of information that meets a first threshold, a candidate selection interface that provides functionality for the user to select an item from recommended candidate items needing the first type of information, a user interface via which the user can provide the first type of information for an item selected by the user, a game system configured to calculate for a game scores and rankings based at least in part on data stored in the data repository.

Methods and systems for searching for and identifying data repository deficits

The present technology may identify item category affinities by identifying a plurality of classifications of an item. An accuracy of the plurality of classifications relative to one another for the item may be identified. A category affinity of the item may be determined based on the accuracy of the plurality of classifications relative to one another.

Video classification

Tag merging enables a hosting entity such as a website to determine one or more tags that are logically-related to a particular tag and to present these tags to users to enable the users to vote whether to merge a logically-related tag with the particular tag. The hosting entity may determine these logically-related tags in multiple ways. For instance, the hosting entity may analyze keyword-to-keyword similarity data, item-overlap data, or may employ stemming logic. When the entity presents these tags to a user, the user may vote to merge the particular tag with one or more of the presented logically-related tags. When merged, items associated with the selected logically-related tag may become associated with the particular tag, or vice versa. Additionally, the selected tag may be removed from the items previously associated with the selected tag, or vice versa.

Tag merging

Tag scoring for elements associated with a common tag enables a user to conduct a tag search and view a listing of elements associated with the tag. The listing can be ordered by each element's tag score. To create such a tag score, users may associate an element with one or more tags that characterize the element. A tag score may then be assigned to this element for each assigned tag and may be based on a multitude of factors. These factors may include a number of times that the element has been tagged with the assigned tag and users' votes on the accuracy of the assigned tag to the element. Tag-scoring factors may include, among others, an age of a tag associated with the element, a click rate for the element, a customer review of the element, a sales rank for the element, or an availability of the element.

Tag scoring for elements associated with a common tag

Growing community of inventors

Seattle, WA, United States of America

Scott Allen Mongrain