Method and system for personalized recommendation of pit labelling

Abstract

The invention discloses a method for the personalized recommendation of pit labelling. The method is characterized by comprising the steps that user browsing information and customer browsing behaviors are collected; according to the user browsing information and the customer browsing behaviors, the weighted values of user preference labels are calculated; each time before the next screen of the commodity flow is loaded, the case that whether or not the conditions of the recommended pit labels of the exhibition are satisfied is evaluated; if the conditions of the pit labels are satisfied, the pit labels of the exhibition are shown. According to the method and system for the personalized recommendation of pit labelling, through the collection, calculation and judgement of user browsing information, personalized recommendations on pit labels for the users are made, so that in the commodity flow viewing processes of the users, the user interest points are captured in real time, and in the screen flipping processes of the users, the user current interest points are displayed aggregately through the selection of appropriate locations, which makes it easy for the users in the browsing processes to timely focus on their own interested commodity information, with no loss of fun in the shopping process of the commodity flow, and user consumption experience is improved.

Description

technical field [0001] The present invention relates to a method and system for recommending pit labels, in particular to a method and system for personalized recommending pit labels. Background technique [0002] At present, the App side of the e-commerce platform usually displays the product collection in the form of product flow, which is also determined by the characteristics of the mobile phone itself. The main methods of existing product flow display include (but are not limited to): [0003] (1) Aggregate all category brands on the whole site, according to a certain matching method, for example, each category occupies three pits in a row, and the categories are arranged in a certain order, and so on. Mixed display of similar category brands Strategy; [0004] (2) Focus on a certain top-level category, such as men’s and women’s clothing, home appliances, etc. There are many types of product subdivisions under the category, so the product queue of a single category is ...

AI Technical Summary

Problems solved by technology

[0007] But the shortcomings are also obvious. When users encounter the categories, brands, and products they are interested in, it is very troublesome to compare them horizontally. Users have to jump out of the current product flow and search or sub-category to find more similar Yes, very inconvenient to operate

Images