CN118121936B - Data processing method and system for real-time game interaction - Google Patents

Abstract

The invention discloses a data processing method and a system for real-time interaction of games, and relates to the technical field of data processing, wherein the method comprises the steps of collecting historical game behavior data of all players entering the same game through a game server; preprocessing the historical game behavior data to obtain preprocessed historical game behavior data; analyzing player gaming behavior threat values and player gaming behavior capability values based on the historical gaming behavior data; obtaining game level of a player and game difficulty; the game map is used for carrying out birth point distribution on all players entering the same game. The invention can increase the interest of the game when the player plays the game, and avoid the two parties losing the most important experience of 'average force and enemy' in the game because of the large difference in the aspects of the game grade, the game style, the capability and the like of the allocated player when the player interacts with the players at the similar positions.

Description

Data processing method and system for real-time game interaction

Technical Field

The present invention relates to the field of data processing technology, and in particular to a data processing method and system for real-time game interaction.

Background technique

With the continuous development of the game market, more and more excellent game works have been launched one after another, and are widely loved by many game enthusiasts. The experience of a game is crucial for players. In competitive games, players form a team to enter the game and are randomly assigned to birth points in different areas of the game map. However, the problem with this random assignment is that if the game ability of another player assigned near the player is too strong, the player will be eliminated too early, thus affecting the player's gaming experience and the excitement of the game. Therefore, how to reasonably allocate birth points to prevent players from losing their gaming experience too early is a technical issue that needs attention at present.

For example, the Chinese patent with the authorization announcement number CN202620680U discloses a somatosensory game controller based on MEMS, including a micro sensor device, a data processing device and a wireless communication device; the micro sensor device includes a three-axis micro accelerometer arranged at the human foot for collecting two-dimensional direction information, a three-axis gyroscope arranged at the human head for collecting perspective information and a three-axis micro accelerometer arranged at the human hand for collecting motion information; the output ends of the three-axis micro accelerometer arranged at the foot, the three-axis micro accelerometer arranged at the hand and the three-axis gyroscope are connected to the input end of the host computer through the data processing device and the wireless communication device in turn. This patent can improve the fun of the game and the happiness of the players. By setting the micro sensor devices in various parts of the limbs, the movement information of the limbs can be collected in real time, and the synchronous interaction between the game player and the game character can be realized, so that the player can get an ideal game experience and have a good fitness effect.

For example, the patent with publication number CN110308787A discloses an AR interactive system and method combining multi-dimensional interactive recognition with chess and card games, including a server, a host, a display unit group, and a human 3D skeleton data acquisition and facial recognition data acquisition group. The host is electrically connected to the server in a two-way manner, the host is electrically connected to the display unit group in an output manner, and the host is electrically connected to the human skeleton data acquisition group in an input manner. The human skeleton data acquisition group collects the player's body shape and generates a 3D skeleton model of the player. At the same time, the human skeleton data acquisition group collects the player's actions in selecting chess and card elements. Through data processing, the player's 3D skeleton model is controlled in real time to select virtual chess and card elements in a virtual scene, avoiding the problem that most current chess and card element games are controlled by a mouse and keyboard, and have poor interactivity with players and game immersion.

The above patents all have the problem raised by the background technology: in the prior art, when players are interacting in real time in the game, they are not assigned to equally matched players in adjacent areas when they first enter the game, resulting in players being eliminated prematurely and losing their gaming experience; to solve these problems, the present invention proposes a data processing method and system for real-time game interaction.

Summary of the invention

In view of the shortcomings of the prior art, the main purpose of the present invention is to provide a data processing method and system for real-time game interaction, which can effectively solve the problems in the background technology. The specific technical solutions of the present invention are as follows:

The data processing method for real-time game interaction includes the following specific steps:

S1. Collect historical game behavior data of all players entering the same game through the game server;

S2, preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;

S3, substituting the historical game behavior data into the player game behavior threat value calculation strategy and the player game behavior ability value calculation strategy to respectively calculate the player game behavior threat value and the player game behavior ability value;

The player game behavior threat value calculation strategy in S3 includes:

S31, before the player plays the current game, extract the historical mouse input data and historical keyboard input data of the player's n games in history, as well as the number of times the player quits the game midway in the historical game data;

S32: Substitute the historical mouse input data and keyboard input data of n games and the number of times the player quits the game into the player game behavior threat value calculation formula to calculate the player game behavior threat value. ;

S33, the player game behavior threat value calculation formula is: , where m is the number of keys required by the player in each game, is the number of mouse clicks by the player in the i-th game, is the success rate of the player clicking the target object in the game in the i-th game, A is the number of times the player quits the game midway, is the number of times the jth key is pressed by the player in the i-th game, is the average time interval between consecutive key presses of the jth key by the player in the i-th game, i is any number from 1 to n, and j is any number from 1 to m;

The player game behavior ability value calculation strategy in S3 includes:

S34, before the player plays the current game, extract the historical keyboard input data and historical game data of the player's n games in history;

S35, substituting the historical keyboard input data and historical game data of n games into the player's game behavior ability value calculation formula to calculate the player's game behavior ability value ;

S36: The calculation formula for the player's game behavior ability value is: , where S is the map area of the game, m is the number of keys required by the player in each game, is the game difficulty of the ith game, is the length of the player's moving path in the i-th game, is the average moving speed of the players in the ith game, is the completion time of the player's ith game, is the number of times the jth key is pressed by the player in the i-th game, is the average time interval between consecutive presses of the jth key by the player in the i-th game, is the area of the map in the ith game, num is the number of games won, i is any one from 1 to n, and j is any one from 1 to m;

S4. Obtain the game difficulty and the game level of the player;

S5, substituting the player's game behavior threat value, the player's game behavior ability value, the game difficulty, and the player's game level into the current game matching score calculation strategy to calculate the player's current game matching score, and establishing a birth point allocation sequence for storing all players who enter the same game in ascending order according to the player's current game matching score, and allocating birth points to the players in the birth point allocation sequence in the game map using a distance formula;

The S5 specifically includes:

S51. Assume that there are Q players in this game, and obtain the minimum game level of the Q players. , the maximum game level of the player ; Get the minimum value of the player's game behavior threat value among Q players The maximum threat value of the player's game behavior , and the minimum value of the player's game behavior ability value The maximum value of the player's game behavior ability ; Substitute the game difficulty of the current game played by the player, the game level of the player, the threat value of the player's game behavior and the ability value of the player's game behavior into the current game matching score calculation strategy to calculate the current game matching score of each player;

S52: The matching score calculation strategy for this game includes: obtaining the maximum game difficulty of the qth player in n games in history. , calculate the game matching score of the qth player ,in They are the game difficulty influence coefficient, the player game level influence coefficient, the player game behavior threat value influence coefficient, and the player game behavior ability value influence coefficient; D is the game difficulty of this game, is the game level of the qth player, is the game behavior threat value of the qth player, is the game behavior ability value of the qth player.

Specifically, the historical game behavior data includes: historical mouse input data, historical keyboard input data, and historical game data; the historical mouse input data includes the number of mouse clicks of the player in each game, the success rate of clicking on the target object in the game, and the average time interval between all two adjacent mouse clicks in each game; the historical keyboard input data includes the number of keys required by the player in each game, the number of times each key is pressed, and the average time interval between each key being pressed continuously; the historical game data includes the completion time of each game of the player, the game difficulty of each game, the number of games won, the number of games where the player quit midway, the map area of each game, the length of the player's movement path in each game, and the average movement speed.

Specifically, the preprocessing in S2 includes: deleting missing values and duplicate values in the data, and normalizing the deleted data.

Specifically, S4 specifically includes: obtaining the game difficulty of the player in multiple games in history, the game level of the player, and the game difficulty and game level of the player in the current game played by the player.

Specifically, the S5 further includes:

S53, evenly divide the current game map into Q areas, obtain the current game matching scores of Q players in the current game and arrange them in ascending order, and store the players corresponding to the current game matching scores arranged in ascending order in a birth point allocation sequence; wherein the first element in the birth point allocation sequence is the player with the smallest current game matching score, and the Qth element is the player with the largest current game matching score; let q=1, and allocate the player corresponding to the first element in the birth point allocation sequence to the center point of any area on the game map;

S54, using the distance formula to calculate the distance between the qth player and the center point of the adjacent area, taking the center point of the adjacent area with the smallest distance as the next allocation position, setting q=q+1, Q=Q-1, and allocating the player corresponding to the qth element in the birth point allocation sequence to the next allocation position;

S55. Repeat S54 until q=Q, completing the allocation of birth points for all players.

Specifically, a data processing system for real-time game interaction is implemented based on the data processing method for real-time game interaction, and the system includes the following modules:

The data collection module is used to collect the historical game behavior data of all players who enter the same game through the game server, and obtain the game difficulty and the game level of the players; and pre-process the historical game behavior data to obtain the pre-processed historical game behavior data;

A data analysis module, used to substitute historical game behavior data into the player game behavior threat value calculation strategy and the player game behavior ability value calculation strategy to calculate the player game behavior threat value and the player game behavior ability value respectively;

The birth point allocation module is used to substitute the player's game behavior threat value, the player's game behavior ability value, the game difficulty, and the player's game level into the current game matching score calculation strategy to calculate the player's current game matching score, establish a birth point allocation sequence, and store all players who enter the same game in ascending order according to the player's current game matching score. The birth point allocation is performed on the game map by using the distance formula.

The control module is used to control the operation of each module.

Compared with the prior art, the present invention has the following beneficial effects:

The present invention collects historical game behavior data of all players who enter the same game through a game server; pre-processes the historical game behavior data to obtain pre-processed historical game behavior data; analyzes the player's game behavior threat value and the player's game behavior ability value based on the historical game behavior data; obtains the game difficulty and the player's game level; and allocates birth points to all players who enter the same game in the game map. The present invention can increase the fun of the game when the player is playing the game, and avoids the loss of the most important "equally matched" experience in the game when the player and the player in the same position interact because of the large differences in the game level, game style, ability, etc. of the allocated players.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flowchart of a data processing method for real-time game interaction according to the present invention;

FIG. 2 is a schematic diagram of modules of a data processing system for real-time game interaction according to the present invention.

Detailed ways

In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

Example 1

This embodiment provides a data processing method for real-time game interaction. The specific scheme is as shown in FIG1 . The data processing method for real-time game interaction includes the following specific steps:

S1. Collect historical game behavior data of all players entering the same game through the game server;

S2, preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;

S3, substituting the historical game behavior data into the player game behavior threat value calculation strategy and the player game behavior ability value calculation strategy to respectively calculate the player game behavior threat value and the player game behavior ability value;

S4. Obtain the game difficulty and the game level of the player;

S5. Substitute the player's game behavior threat value, the player's game behavior ability value, the game difficulty, and the player's game level into the current game matching score calculation strategy to calculate the player's current game matching score, and establish a birth point allocation sequence for storing all players entering the same game in ascending order according to the player's current game matching score, and allocate birth points to the players in the birth point allocation sequence in the game map through the distance formula.

In this embodiment, the historical game behavior data includes: historical mouse input data, historical keyboard input data, and historical game data; the historical mouse input data includes the number of mouse clicks of the player in each game, the success rate of clicking on the target object in the game, and the average time interval between all two adjacent mouse clicks in each game; the historical keyboard input data includes the number of keys required by the player in each game, the number of times each key is pressed, and the average time interval between consecutive presses of each key; the historical game data includes the completion time of each game of the player, the game difficulty of each game, the number of games won, the number of games where the player quits midway, the area of the map of each game, the length of the player's movement path in each game, and the average movement speed.

In this embodiment, the preprocessing in S2 includes: deleting missing values and duplicate values in the data, and normalizing the deleted data.

In this embodiment, the player game behavior threat value calculation strategy in S3 includes:

S31, before the player plays the current game, extract the historical mouse input data and historical keyboard input data of the player's n games in history, as well as the number of times the player quits the game midway in the historical game data;

S32: Substitute the historical mouse input data and keyboard input data of n games and the number of times the player quits the game into the player game behavior threat value calculation formula to calculate the player game behavior threat value. ;

S33, the player game behavior threat value calculation formula is: , where m is the number of keys required by the player in each game, is the number of mouse clicks by the player in the i-th game, is the success rate of the player clicking the target object in the game in the i-th game, A is the number of times the player quits the game midway, is the number of times the jth key is pressed by the player in the i-th game, is the average time interval between consecutive pressing of the j-th key by the player in the i-th game, where i is any number from 1 to n and j is any number from 1 to m.

In this embodiment, the player game behavior ability value calculation strategy in S3 includes:

S34, before the player plays the current game, extract the historical keyboard input data and historical game data of the player's n games in history;

S35, substituting the historical keyboard input data and historical game data of n games into the player's game behavior ability value calculation formula to calculate the player's game behavior ability value ;

S36: The calculation formula for the player's game behavior ability value is: , where S is the map area of the game, m is the number of keys required by the player in each game, is the game difficulty of the ith game, is the length of the player's moving path in the i-th game, is the average moving speed of the players in the ith game, is the completion time of the player's ith game, is the number of times the jth key is pressed by the player in the i-th game, is the average time interval between consecutive presses of the jth key by the player in the i-th game, is the area of the map for the i-th game, num is the number of games won, i is any one from 1 to n, and j is any one from 1 to m.

In this embodiment, S4 specifically includes: obtaining the game difficulty of the player in multiple games in history, the game level of the player, and the game difficulty and game level of the player in the current game played by the player.

In this embodiment, S5 specifically includes:

S51. Assume that there are Q players in this game, and obtain the minimum game level of the Q players. , the maximum game level of the player ; Get the minimum value of the player's game behavior threat value among Q players The maximum threat value of the player's game behavior , and the minimum value of the player's game behavior ability value The maximum value of the player's game behavior ability ; Substitute the game difficulty of the current game played by the player, the game level of the player, the threat value of the player's game behavior and the ability value of the player's game behavior into the current game matching score calculation strategy to calculate the current game matching score of each player;

S52: The matching score calculation strategy for this game includes: obtaining the maximum game difficulty of the qth player in n games in history. , calculate the game matching score of the qth player ,in They are respectively the game difficulty influence coefficient, the player game level influence coefficient, the player game behavior threat value influence coefficient, and the player game behavior ability value influence coefficient. It should be noted that the game difficulty influence coefficient, the player game level influence coefficient, the player game behavior threat value influence coefficient, and the player game behavior ability value influence coefficient need to be determined by those skilled in the art according to specific application requirements and actual conditions; D is the game difficulty of this game, is the game level of the qth player, is the game behavior threat value of the qth player, is the game behavior ability value of the qth player.

In this embodiment, S5 specifically further includes:

S53, evenly divide the current game map into Q areas, obtain the current game matching scores of Q players in the current game and arrange them in ascending order, and store the players corresponding to the current game matching scores arranged in ascending order in a birth point allocation sequence; wherein the first element in the birth point allocation sequence is the player with the smallest current game matching score, and the Qth element is the player with the largest current game matching score; let q=1, and allocate the player corresponding to the first element in the birth point allocation sequence to the center point of any area on the game map;

S54, using the distance formula to calculate the distance between the qth player and the center point of the adjacent area, taking the center point of the adjacent area with the smallest distance as the next allocation position, setting q=q+1, Q=Q-1, and allocating the player corresponding to the qth element in the birth point allocation sequence to the next allocation position;

S55. Repeat S54 until q=Q, completing the allocation of birth points for all players.

Example 2

This embodiment provides a data processing system for real-time game interaction. The specific scheme is as shown in FIG2 . The data processing system for real-time game interaction is implemented based on the data processing method for real-time game interaction described in Embodiment 1. The system includes the following modules:

The data collection module is used to collect the historical game behavior data of all players who enter the same game through the game server, and obtain the game difficulty and the game level of the players; and pre-process the historical game behavior data to obtain the pre-processed historical game behavior data;

A data analysis module, used to substitute historical game behavior data into the player game behavior threat value calculation strategy and the player game behavior ability value calculation strategy to calculate the player game behavior threat value and the player game behavior ability value respectively;

The birth point allocation module is used to substitute the player's game behavior threat value, the player's game behavior ability value, the game difficulty, and the player's game level into the current game matching score calculation strategy to calculate the player's current game matching score, establish a birth point allocation sequence, and store all players who enter the same game in ascending order according to the player's current game matching score. The birth point allocation is performed on the game map by using the distance formula.

The control module is used to control the operation of each module.

The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims (6)

1. The data processing method for game real-time interaction is characterized by comprising the following steps of: the method comprises the following specific steps:

s1, collecting historical game behavior data of all players entering the same game through a game server;

s2, preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;

S3, substituting the historical game behavior data into a game behavior threat value calculation strategy and a game behavior capacity value calculation strategy of the player to calculate a game behavior threat value and a game behavior capacity value of the player respectively;

The player game action threat value calculation strategy in the S3 comprises the following steps:

S31, before the player plays the game, extracting historical mouse input data and historical keyboard input data of n times of games of the player in history and the number of times of games of the player in the historical game data to exit halfway;

s32, substituting the historical mouse input data and the historical keyboard input data of the n-time games and the number of times of midway exiting the game of the player into a game behavior threat value calculation formula of the player to calculate a game behavior threat value of the player ；

S33, the player game behavior threat value calculation formula is as followsWhere m is the number of keys required by the player in each game,For the number of mouse clicks of the player in the ith game,The success rate of clicking the target object in the game in the ith game by the player, the number of games which the player exits halfway by A,For the number of times the jth key position is pressed in the ith game by the player,For an average time interval in which a jth key position is continuously pressed in an ith game by a player, i is any one of 1 to n, j is any one of 1 to m;

the player game behavior ability value calculation strategy in the S3 comprises the following steps:

S34, before the player plays the game, extracting historical keyboard input data and historical game data of n times of games of the player historically;

s35, substituting the historical keyboard input data of the n games and the historical game data into a player game behavior capability value calculation formula to calculate the player game behavior capability value ；

S36, the player game behavior ability value calculation formula is as followsWherein S is the area of the game map, m is the number of keys required by the player in each game,Game difficulty of the ith game,To move the path length of the player in the ith game,To the average moving speed of the player in the ith game,For the completion time of the ith game of the player,For the number of times the jth key position is pressed in the ith game by the player,An average time interval for the player to continuously key the jth key position in the ith game,For the i-th game map area, num is the number of winning games, i is any one of 1 to n, j is any one of 1 to m;

s4, obtaining game difficulty and game grades of players;

S5, substituting the game behavior threat value of the player, the game behavior capability value of the player, the game difficulty and the game level of the player into a game matching score calculation strategy of the player to calculate the game matching score of the player, and establishing a birth point distribution sequence for storing all players entering the same game according to the game matching score ascending sequence of the player, and performing birth point distribution on the players in the birth point distribution sequence in a game map through a distance formula;

The step S5 specifically comprises the following steps:

s51, setting Q players in the game field, and obtaining the game level minimum value of the players in the Q players Maximum value of game level of player; Obtaining minimum value of threat values of game behaviors of players in Q playersAnd player game action threat value maximumAnd a player game performance capability value minimumAnd player game performance capability value maximum; Substituting the game difficulty of the game played by the player, the game level of the player, the game behavior threat value of the player and the game behavior capability value of the player into a game matching score calculation strategy to calculate the game matching score of each player;

S52, the local game matching score calculation strategy comprises the following steps: obtaining maximum game difficulty in n-time game of the qth player in history Computing a game match score for the q-th playerWhereinThe game difficulty influence coefficient, the player game level influence coefficient, the player game behavior threat value influence coefficient and the player game behavior capacity value influence coefficient are respectively; d is the game difficulty of the game field,For the game level of the q-th player,Player game play threat values for the q-th player,Player gaming behavior capability values for the qth player.

2. The data processing method for game real-time interaction according to claim 1, wherein: the historical game behavior data includes: historical mouse input data, historical keyboard input data and historical game data; the historical mouse input data comprises the number of mouse clicks of a player in each game, the success rate of clicking on a target object in the game and the average value of time intervals between all adjacent two mouse clicks in each game; the historical keyboard input data comprises the number of keys required by a player in each game, the number of times each key is pressed and the average time interval of each key being continuously pressed; the historical game data includes the completion time of each game of the player, the game difficulty of each game, the number of games that earn winnings, the number of games that the player exits halfway, the map area of each game, the length of the player's movement path in each game, and the average movement speed.

3. The data processing method for game real-time interaction according to claim 2, wherein: the preprocessing in S2 includes: deleting the missing value and the repeated value in the data, and carrying out normalization processing on the deleted data.

4. A data processing method for real-time interaction of a game according to claim 3, wherein: the step S4 specifically comprises the following steps: the game level of the player, the game level of the player's own game, and the game level of the player are obtained.

5. The data processing method for game real-time interaction according to claim 4, wherein: the step S5 specifically further comprises:

S53, uniformly dividing the game map into Q areas, acquiring game matching scores of Q players in the game, arranging in ascending order, and storing the players corresponding to the game matching scores after the ascending order into a birth point distribution sequence; the first element in the birth point distribution sequence is a player with the minimum matching score of the game, and the Q element is a player with the maximum matching score of the game; let q=1, allocate the player corresponding to the first element in the birth point allocation sequence to the center point of any area on the game map;

S54, calculating the distance between the qth player and the center point of the adjacent area by using a distance formula, taking the center point of the adjacent area with the smallest distance as the next allocation position, letting q=q+1, and Q=Q-1, and allocating the player corresponding to the qth element in the birth point allocation sequence to the next allocation position;

S55, repeating S54 until q=q, and completing the birth point allocation of all players.

6. Data processing system for game real-time interaction, realized on the basis of the data processing method for game real-time interaction according to any one of claims 1-5, characterized in that: the system comprises the following modules:

the data acquisition module is used for acquiring historical game behavior data of all players entering the same game through the game server, and acquiring game difficulty and game grades of the players; preprocessing the historical game behavior data to obtain preprocessed historical game behavior data;

The data analysis module is used for substituting the historical game behavior data into a game behavior threat value calculation strategy of the player and calculating the game behavior threat value and the game behavior capacity value of the player respectively;

The game matching score calculation module is used for calculating the game matching score of the player by substituting the game action threat value of the player, the game action capacity value of the player, the game difficulty and the game grade of the player into the game matching score calculation strategy, establishing a game point distribution sequence, and storing all players entering the same game according to the game matching score ascending sequence of the player, and carrying out game point distribution on the players in the game point distribution sequence in a game map through a distance formula;

And the control module is used for controlling the operation of each module.