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Method and apparatus for collaborative filtering for real-time recommendation

A user and user rating technology, applied in data processing applications, special data processing applications, instruments, etc., can solve problems such as unavailable user data, service or application collection, etc.

Inactive Publication Date: 2014-04-02
NOKIA TECHNOLOGLES OY
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, such user data is often not available or has not been collected in relation to a particular service or application

Method used

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  • Method and apparatus for collaborative filtering for real-time recommendation
  • Method and apparatus for collaborative filtering for real-time recommendation
  • Method and apparatus for collaborative filtering for real-time recommendation

Examples

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Embodiment Construction

[0023] Disclosed are examples of methods, apparatus, and computer programs that generate one or more recommendations for one or more users based at least in part on historical user ratings and / or preferences generated by considering historical interactions with one or more content items. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the invention. It is apparent, however, to one skilled in the art that the embodiments of the invention may be practiced without these specific details or with an equivalent arrangement. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring the embodiments of the invention.

[0024] As used herein, the term content item refers to any item of interest such as, for example but not limited to, any person, place or thing, restaurant, coupon, event, special offer, st...

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Abstract

An approach is provided for generating one or more recommendations to a user based on interactions the user may have with items or topics of interest. The approach involves processing and / or facilitating a processing of one or more interactions of a user with one or more content items. The approach further involves causing, at least in part, an accumulation of the one or more processed interactions of the user. The approach also involves causing, at least in part, a determination of one or more user preferences based, at least in part, on the accumulated one or more processed interactions. The approach additionally involves causing, at least in part, a generation of a rating score of the user for the topic based, at least in part, on the one or more user preferences.

Description

Background technique [0001] Service providers and device manufacturers (eg, wireless, cellular, etc.) are constantly challenged to provide value and convenience to consumers by, for example, providing compelling network services. One area of ​​development has been the use of recommender systems to provide users with suggestions or recommendations for content, items, etc. (e.g., about people, places or things of interest, such as companions, restaurants, Recommendations for stores, holidays, movies, VODs, books, songs, software, articles, news, pictures, etc.). For example, a typical recommender system can suggest items to a user based on a prediction that the user will be interested in the item by comparing the user's preferences with one or more reference features—even if the user has never considered the item before. Such recommender systems have historically and been based on collaborative filtering, which typically relies on large amounts of user data (eg, historical expl...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F17/30867G06Q30/0627G06F16/9535
Inventor 杜楠田继雷
Owner NOKIA TECHNOLOGLES OY
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