Game prop personalized recommendation method

A recommendation method and technology of game props, which are applied in the field of personalized recommendation of game props, can solve the problems of increasing the amount of calculation, the difference of props is great, the distance is large, etc., and achieve the effect of improving the accuracy and reducing the amount of calculation.

Inactive Publication Date: 2016-03-30
SNAIL GAMES
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, since the props of online games are all virtual items, the data characteristics of online games are very different from those of e-commerce, so moving the recommendation algorithm of e-commerce to online game data will inevitably cause discomfort
The currently public ItemCF algorithm is based on the items (Item) that the user has already purchased. First, calculate the distance matrix between items and then recommend new items (Item) to each user. This calculation method is directly applied to There are the following disadvantages in online game data...

Method used

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  • Game prop personalized recommendation method

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Experimental program
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Embodiment 1

[0049] The game item personalized recommendation method of the present invention will be described in detail below in conjunction with Embodiment 1:

[0050] Step 201, extracting data,

[0051] (1) Recharge data: the recharge amount of the player in the last 6 months.

[0052] (2) Login data: the number of login days and total online time of the player in the last 3 months.

[0053] (3) Level data: the player's current role level, life occupation level

[0054] (4) Gameplay data: the number of times players have participated in each game in the last 3 months

[0055] (5) Transaction data: in the last 3 months, the number of transactions between players in the game and the transaction official bank

[0056] (6) Consumption data: the quantity and amount of each item purchased by the player in the last 3 months

[0057] Step 202, clean the data (only for recharge, login, level, gameplay, transaction data),

[0058] (1) Delete the record with N_EXT_ID=-1.

[0059] (2) Delete...

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Abstract

The present invention relates to a game prop personalized recommendation method, comprising: carrying out extraction, cleaning and processing on data; mapping the data into a low-dimensional space from an input space; classifying the data to partition players into different categories; and recommending props which are most possibly bought by each player for the player. According to the game prop personalized recommendation method disclosed by the present invention, a calculated amount of a recommendation algorithm is greatly reduced, prop recommendation accuracy is significantly improved, and a user experience effect of a network game is promoted.

Description

technical field [0001] The invention relates to the field of online games, in particular to a method for personalized recommendation of game props. Background technique [0002] In existing online games, there are numerous game props. The following three technologies are usually used to realize the personalized recommendation of game props: (1) data dimensionality reduction technology; (2) classification algorithm; (3) recommendation algorithm. Each algorithm technology plays a crucial role in the game item recommendation algorithm. The three algorithms are combined into an algorithm system, and none of them is dispensable. [0003] Among them, the data dimensionality reduction technology needs to solve the complex problem of game data. Because the game data itself has some non-traditional characteristics, such as: game data sources are complex, data types are diverse, data dimensions are high (hundreds or thousands), and data is massive. Therefore, before using the recom...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/9535G06F18/23213
Inventor 黄付杰
Owner SNAIL GAMES
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