Personalized food recommendation method based on commodity forest system

A recommendation method and product technology, applied in marketing and other directions, can solve the problem of no separation of products and merchants

Inactive Publication Date: 2013-10-09
HUNAN UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0004] Relatively speaking, there are few applications in the food industry at present, and there is no separation of commodities and merchants, each of which is processed and modeled separately

Method used

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  • Personalized food recommendation method based on commodity forest system
  • Personalized food recommendation method based on commodity forest system
  • Personalized food recommendation method based on commodity forest system

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Embodiment Construction

[0034] The technical solutions of the present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0035] exist figure 1 Among them, the food recommendation LBS system in the present invention is divided into two branches for recommendation, which are respectively User-Item-Shop and User-Shop-Item.

[0036] In the User-Item-Shop branch, it is further divided into items that the user has collected, rated, and browsed and exists in the leaf node, and items that the user has collected, rated, and browsed but do not exist in the leaf node. For the former case, through ItemCF and UserCF performs computational recommendation. When using ItemCF, combine item-user (Item-User) collection, scoring, browsing matrix and item forest system to calculate items with higher similarity and generate item-item (Item-Item) similarity matrix; then use The predictive scoring algorithm calculates the degree of interest of the user's product, and...

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Abstract

The invention relates to a personalized food recommendation method based on a commodity forest system. The method includes the following steps of firstly, conducting the following concept definition on the system; secondly, calculating user scores through a UserCF; thirdly, calculating the user cores through an ItemCF. With the current position of a user, the preference of the user and the behavioral habits of the user and the like taken into consideration, personalized restaurants and dishes which meet requirements of the user are recommended to the user, and the food recommendation efficiency and accuracy are improved. Meanwhile, accurate recommendation results can be converted into consuming behaviors, and the user satisfaction degree and merchant benefits are improved.

Description

technical field [0001] The invention belongs to the technical field of e-commerce, and relates to a personalized food recommendation method based on a commodity forest system. Background technique [0002] In recent years, due to the increasing popularity of mobile terminals, the acquisition and push of information resources occurs "anytime, anywhere, and with you". Location-based mobile recommendation systems have become one of the most active research areas in the field of recommendation system research. [0003] The existing ones mainly focus on the recommendation of movies, music, and books, such as mobile blog recommendation, and the m-CCS system proposed by Chiu PH, Kao GYM, etc. Clustering, by analyzing the browsing records of mobile users' blog posts, obtain mobile users' preferences for different types of blog posts, and consider the click-through rate of Internet users on blog posts, and recommend blog posts with high click-through rates and user preferences to mob...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
Inventor 陈浩欧阳跃祁李睿姚明东
Owner HUNAN UNIV
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