Amazon Technologies, Inc.

Abhishek Dubey

James Marvin Freeman, Ii

Joshua B Barnard

Andrew J Watts

Stephen A Slotnick

Aaron Michael Bromberg

Richard Judd Winograd

Peter Wei-Chih Chen

Bryant F Herron-Patmon

Nush Karmacharya

Lei Li

Vijay Sen

Gregory Scott Benjamin

Andrew Ma

Michael Sean Mayo

Neeti Gupta

Meltem Celikel

Darryl Hudgin

Brent M Barkman

Gurpreet Singh Ahluwalia

Sachin Shah

Prateek Rameshchandra Shah

Cody Wayne Maxwell Powell

Travis M Grigsby

Rama Ajit Karve

James Marvin Freeman

Ii James Marvin Freeman

Anddrew J Watts

Disclosed are various embodiments for analyzing searches of verbal media content associated with media content features. A relatively popular portion of a media content item is determined based at least in part on a dialogue of the relatively popular portion of the media content item being included in a plurality of dialogue search queries received from a plurality of client devices. The media content item is rendered via a client device, and a recommendation for an item is via the client device in response to the relatively popular portion of the media content item being rendered.

Analyzing user searches of verbal media content

Disclosed are various embodiments for predictive caching of content to facilitate instantaneous use of the content. If a user is likely to commence use of a content item through a client, and if the client has available resources to facilitate instantaneous use, the client is configured to predictively cache the content item before the user commences use. In doing so, the client may obtain metadata for the content item from a server. The client may then initialize various resources to facilitate instantaneous use of the content item by the client based at least in part on the metadata.

Predictive caching for content

Disclosed are various embodiments for predictive caching of content to facilitate use of the content. If account is likely to commence use of a content item, the content item is cached before the use is commenced. The cache may be divided into multiple segments with different content selection criteria.

Segmented predictive caching for content

Disclosed are various embodiments for client-side predictive caching of content to facilitate use of the content. If account is likely to commence use of a content item through a client, the client is configured to predictively cache the content item before the use is commenced. In doing so, the client may obtain an initial portion of the content item from another computing device. The client may then initialize various resources to facilitate use of the content item by the client. The client-side cache may be divided into multiple segments with different content selection criteria.

Client-side predictive caching for content

Disclosed are various embodiments for analyzing searches of verbal media content associated with media content features. Custom abridgements of media content features may be generated based on user interest in a plurality of portions of the media content feature following the plurality of verbal media content searches. A recommendation for a portion of a media content feature may be sent to a first client based on an expression of interest by a second client in dialog featured in the portion of the media content feature but in a secondary language. The first client may be determined based on an association between the first client and the secondary language. A product can be recommended to a client based on a dialog search query, where the dialog of a media content search result contains a reference to the product or a similar product.

Disclosed are various embodiments for client-side predictive caching of content to facilitate instantaneous use of the content. If a user is likely to commence use of a content item through a client, the client is configured to predictively cache the content item before the user commences use. In doing so, the client may obtain metadata for the content item and an initial portion of the content item from another computing device. The client may then initialize various resources to facilitate instantaneous use of the content item by the client based at least in part on the metadata and the initial portion. The client-side cache may be divided into multiple segments with different content selection criteria.

Disclosed are various embodiments for predictive caching of content to facilitate instantaneous use of the content. If a user is likely to commence use of a content item through a client, and if the client has available resources to facilitate instantaneous use, the client is configured to predictively cache the content item before the user commences use. In doing so, the client may obtain metadata for the content item and an initial portion of the content item from a server. The client may then initialize various resources to facilitate instantaneous use of the content item by the client based at least in part on the metadata and the initial portion.

Disclosed are various embodiments for analyzing user searches of verbal media content associated with media content features. A search query is obtained from a user. Media content items are determined by executing a verbal media content search based at least in part on the search query. The media content items include verbal media content that is relevant to the search query. Data relating to the verbal media content search is stored. A user interest in media content is determined by analyzing the data relating to the verbal media content search.

Disclosed are various embodiments for generating implicit user ratings for a media item. A ratings analyzer tracks user interaction with a network content server configured to present a media item to a plurality of users and then generates an interaction history for each user based at least upon corresponding user interaction with the media item presented by the network content server. A user interaction metric may be generated based at least upon each interaction history associated with the plurality of users and a user interface may be encoded for display where the user interface comprises the user interaction metric.

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Seattle, WA, United States of America

Abhishek Dubey