Cellphone model recommendation system based on collaborative filtering recommendation algorithm

A collaborative filtering recommendation and recommendation method technology, applied in marketing and other directions

Inactive Publication Date: 2015-07-22
NANJING UNIV
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  • Abstract
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  • Claims
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AI Technical Summary

Problems solved by technology

Provide recommendation services to users through the user interest preference model, but it has certain limitations.

Method used

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  • Cellphone model recommendation system based on collaborative filtering recommendation algorithm
  • Cellphone model recommendation system based on collaborative filtering recommendation algorithm
  • Cellphone model recommendation system based on collaborative filtering recommendation algorithm

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Experimental program
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Embodiment Construction

[0048] The present invention will be described in detail below in conjunction with the accompanying drawings.

[0049] like figure 1 As shown, the recommendation system extracts the required user information and model information data by querying the database. After preprocessing such as data normalization and formatting, it first calculates the nearest neighbor of the target user, then scores the model through the nearest neighbor, and finally generates Recommend results and make recommendations to target users.

[0050] The flow chart of the model recommendation system based on the mixed information collaborative filtering algorithm of the present invention is as follows figure 2 shown.

[0051] Step 0 is the initial step of the present invention;

[0052] In the nearest neighbor calculation stage (steps 1-3), step 1 is to extract user information and model information from the database for normalization, remove outliers, and exclude users and models that do not meet the...

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Abstract

The invention discloses a cellphone model recommendation system based on a collaborative filtering recommendation algorithm. According to the cellphone model recommendation system, cellphone models are accurately recommended to users according a cellphone model life cycle model and a corresponding scoring function by the aid of a framework of the collaborative filtering recommendation algorithm. A method for the cellphone model recommendation system includes a nearest neighbor calculation stage and a cellphone model recommendation stage. In the nearest neighbor calculation stage, data are preprocessed, noise and abnormal data are cleared away, unqualified users and cellphone models are eliminated, current active personal information and historical consumption information of users are extracted from a user database, and related attributes of cellphone models currently used by the users are extracted from a cellphone model database; corresponding information is attracted to create a corresponding user vector for each user according to the preprocessed data, and similarities between users are calculated according to the method designed for the system; the similarities between a target user and other users are calculated and the prior N users with highest similarities are taken as nearest neighbors of the target user.

Description

technical field [0001] The invention relates to establishing a model recommendation system based on operator data. The system uses the framework of a collaborative filtering recommendation algorithm, combines model life cycle models and corresponding scoring functions to recommend models for users. Background technique [0002] With the rapid development of database technology and the wide application of database management systems, more and more data are accumulated. Faced with the surge of data, people hope to dig out many important information hidden behind, so that these data can be better used to serve people. Operators have a large amount of personal information and historical consumption data related to users. How to use these data to create new benefits is a problem operators face, and using these data to recommend mobile phone models to users is such a typical application. [0003] The recommendation methods of recommendation system mainly include content-based fil...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
Inventor 吴骏苗霁彭岳戴恒宇王崇骏李宁
Owner NANJING UNIV
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