How do shopping stations and video stations guess your favorite functions?

how do shopping stations and video stations guess your favorite functions?

Apr.28,2021

tag all goods and videos, which are generally defined by the website itself.
then count the preferences of users or a group of users corresponding to certain characteristics (the tags corresponding to the products or videos they like), and recommend the products and videos corresponding to the tags according to the preferences of users / groups.
General websites may also intervene manually, add manually to increase the weight of goods, and put some products or videos that they want to sell into the recommendation.


I have done a similar function, which is a joke type. I am based on the user's likes, favorites, comments, sharing and other operations, and then analyze all the tags, and then push similar content.


K-nearest neighbor algorithm (KNN) learn about


A users like goods AMagi B. B likes goods B
, so An and B have similar preferences, then A may like goods C
the common algorithm is Collaborative Filter, there are many mature wheels available

MySQL Query : SELECT * FROM `codeshelper`.`v9_news` WHERE status=99 AND catid='6' ORDER BY rand() LIMIT 5
MySQL Error : Disk full (/tmp/#sql-temptable-64f5-1b376d2-2c075.MAI); waiting for someone to free some space... (errno: 28 "No space left on device")
MySQL Errno : 1021
Message : Disk full (/tmp/#sql-temptable-64f5-1b376d2-2c075.MAI); waiting for someone to free some space... (errno: 28 "No space left on device")
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