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Processing method and system of Internet of Things electronic commerce shopping data

An e-commerce shopping and processing method technology, applied in the field of Internet of Things e-commerce shopping data processing, can solve the problems of increasing user evaluation data, data sparse scalability, and reducing the amount of calculation, so as to reduce the amount of calculation and shorten the calculation time. , the effect of increasing the evaluation data

Inactive Publication Date: 2017-04-05
HUBEI UNIV
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The present invention solves the problems of data sparsity and expansibility in the prior art by providing a processing method and system for e-commerce shopping data of the Internet of Things, and realizes the technical effect of increasing user evaluation data and reducing calculation amount

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  • Processing method and system of Internet of Things electronic commerce shopping data
  • Processing method and system of Internet of Things electronic commerce shopping data
  • Processing method and system of Internet of Things electronic commerce shopping data

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Embodiment Construction

[0042] The embodiment of the present invention solves the data sparsity and scalability problems in the prior art by providing a processing method and system for Internet of Things e-commerce shopping data, and realizes the technical effect of increasing user evaluation data and reducing calculation amount .

[0043] The technical solution in the embodiment of the present invention is to solve the above-mentioned technical problems, and the general idea is as follows:

[0044] The user data is first grouped, and then the grouped user data most similar to the target user is obtained, and then the rating data of the target user is obtained according to the most similar grouped user data, thereby increasing the evaluation data of the target user. In addition, in the embodiment of the present invention, user data is grouped, and data analysis is performed in units of groups, thereby reducing the amount of computation and further shortening the computation time.

[0045] In order ...

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Abstract

The invention discloses a processing method and system of Internet of Things electronic commerce shopping data. The method includes: grouping user data; obtaining the grouped user data which is the most similar to target users; and obtaining score data of the target users according to the most similar grouped user data so that evaluation data of the target users is increased. Besides, according to the method and system, the user data is grouped, data analysis is conducted by regarding the group as the unit, the calculation amount is reduced, and the operation time is shortened.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method and system for processing e-commerce shopping data of the Internet of Things. Background technique [0002] Currently, RecSys (Recommender Systems, recommendation system) is widely used in various e-commerce platforms. The CF algorithm (Collaborative Filtering, collaborative filtering algorithm) is one of the most widely used technologies in RecSys, and is the core algorithm of RecSys. The CF algorithm needs to find out the user's preference based on the user's historical behavior, and does not depend on the feature attributes of the item to generate recommendations. Nowadays, the scale of e-commerce system and the number of users are rapidly expanding, and the rating information such as user rating matrix is ​​also huge, and some problems of CF algorithm are gradually exposed, and the quality of the algorithm is gradually declining. The main problem is describ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06K9/62
CPCG06Q30/0203G06F18/214
Inventor 黄辰王时绘张龑
Owner HUBEI UNIV