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Crowd-sourcing and contextual reclassification of rated content

A content, crowdsourcing technique applied in the field of crowdsourcing and context reclassification of rated content to solve the problems of boredom, not guaranteed to be liked by older people, etc.

Inactive Publication Date: 2012-12-05
MICROSOFT TECH LICENSING LLC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Just because millions of teens like a particular content item doesn't guarantee that older adults will like that content item
Likewise, what is humorous in one country or language may appear boring, or worse, offensive in another

Method used

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  • Crowd-sourcing and contextual reclassification of rated content
  • Crowd-sourcing and contextual reclassification of rated content
  • Crowd-sourcing and contextual reclassification of rated content

Examples

Experimental program
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Embodiment Construction

[0013] A content rating system is described herein that enables end users and organizations to share their interpretations of automatically generated opinion scores. The system can provide a simple visual mechanism, such as a slider bar, that the user can move to indicate agreement or disagreement with the automated scoring. The system adds metadata tracking information about the user to the revised score to account for different demographic contexts based on the user's feedback. For example, the system allows administrators to later determine how content is perceived by users of a certain age range, gender, social status, etc. The system performs re-scoring of user-provided ratings taking into account the context, and then presents the re-scored values ​​on a context-specific endpoint. A content rating system provides a crowd-sourcing scheme that scales extremely well, adds more precision (since the scoring is done by individuals within a known demographic category / context),...

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PUM

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Abstract

A content evaluation system is described herein that empowers end users and organizations to share their interpretation of an automatically generated sentiment score. The system provides a control that a user can move to indicate agreement or disagreement with an automatic score. The system adds metadata to a revised score based on the user's feedback that tracks information about the user to consider different demographic contexts. The system performs rescoring with the user-provided scores with contextual consideration, and then exposes the rescored values on context specific endpoints. The system provides a crowd-sourcing approach that scales extremely well, adds more accuracy because individuals within known demographic categories / contexts do the scoring, and generates value-added data products that can be sold / re-sold.

Description

Background technique [0001] The Internet is filled with many different types of content, such as text, video, audio, and so on. Many sources produce content, such as traditional media outlets (eg, news sites), personal blogs, retail stores, product manufacturers, and the like. Some websites aggregate information from other sites. For example, using Really Simple Syndication (RSS) feeds, website authors make content consumable by other sites or users, and syndication sites can consume various RSS feeds to provide syndicated content. [0002] Content publishers often provide tools for rating content or receiving opinions (eg, positive, negative, or some scale in between) about the content from users. For example, a video may include a display of five stars that a user may click to rate the video from one to five stars. Publishers can also display ratings based on input from multiple users and use ratings in searches (eg, to return the highest rated content or to sort content ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F17/30867G06Q30/0282G06F16/9535G06F16/9536
Inventor M·E·墨求里
Owner MICROSOFT TECH LICENSING LLC
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