Random special effect calling method based on virtual gift giving and chat room platform

Abstract

The invention discloses a random special effect calling method based on virtual gift giving and a chat room platform, and relates to the field of computers based on specific calculation models.The chat room platform constructs a specific calculation model according to historical behavior data of a gift sender and current behavior data of the gift sender and a gift receiver; when the user gives the virtual gift, the additional random special effect is probably triggered based on the specific calculation model, and the random special effect giving the virtual gift is associated with the behavior data of the user, so that the interestingness and interaction of the chat room platform are improved.

Description

Technical Field

[0001] The present invention relates to the computer field based on a specific computing model, and in particular to a random special effect calling method based on virtual gift giving and a chat room platform. Background Art

[0002] With the rapid development of Internet technology, the field of social entertainment has ushered in unprecedented changes, especially the popularization of chat room functions, which has greatly enriched the user's online interactive experience. In these virtual spaces, the interaction between users is not only an exchange of information, but also an expression of emotion and the construction of a sense of community belonging. In the prior art, chat room platforms have enabled users to express their love and support for each other by giving each other virtual gifts, but this traditional way of giving virtual gifts often appears to be single and lacks innovation, and it is difficult to meet users' pursuit of freshness and fun. The traditional virtual gift giving behavior is not sufficiently related to the user's historical behavior data on the platform, and the user's sense of interaction is poor.

[0003] Therefore, it is necessary to design a random special effects calling method based on virtual gift giving, and to create a computer-readable calling system based on a specific computing model for random special effects, so as to enhance the fun and freshness of the chat room platform, strengthen the correlation between virtual gift giving behavior and the user's historical behavior data on the platform, and enhance the interactive sense of the platform. Summary of the invention

[0004] The purpose of the present invention is to provide a random special effect calling method and a chat room platform based on virtual gift giving, which aims to overcome the problems existing in the prior art.

[0005] To achieve the purpose, the present invention provides the following technical solutions: A method for calling random special effects based on virtual gift giving, comprising the following steps: Step (1), the platform pre-configures a random special effect library; the random special effect library includes a plurality of special effect sets, and each special effect set is configured with a first-level threshold interval; each special effect set includes at least one special effect subset, and each special effect subset is configured with a second-level threshold interval, and each special effect subset includes at least one special effect element; Step (2), the platform collects and analyzes the user's historical behavior data over the past period of time; Step (3), set a weight for each item of behavior data, and calculate the single weighted score of each item of user's behavior data; Step (4), when a user gives a virtual gift on the platform, the current behavior data of the gift giver and the gift receiver are collected and analyzed; the first-level weighted score is calculated using the current behavior data of the gift giver and the gift receiver; Step (5), determining whether the first-level weighted score is within one of the first-level threshold intervals; if so, the platform selects a special effect set corresponding to the first-level threshold interval from the random special effect library; if not, ending; Step (6), using the historical behavior data of the gift giver, calculate the secondary weighted score; Step (7), determining whether the secondary weighted score is within one of the secondary threshold intervals; if so, the platform selects a special effect set corresponding to the secondary threshold interval from the random special effect library; if not, the process ends; Step (8): the platform calls the special effect elements of the special effect set selected in step (7), and displays them to one or more of the gift giver, the gift receiver, and the remaining platform users through the user-side electronic device.

[0006] Furthermore, in step (1), a random factor threshold interval for selecting the special effect set is also configured for each special effect set; The step (5) is replaced by the following content: determine whether the first-level weighted score is within the first-level threshold interval of one of the special effect sets; if not, end; if so, the platform randomly generates a random factor; further determine whether the random factor is within the random factor threshold interval of the same special effect set; if so, select the special effect set corresponding to the first-level threshold interval; if not, end.

[0007] Furthermore, in step (4), the current behavior data includes the gift type of the current virtual gift at the gift sender and the gift type of the current virtual gift at the gift receiver.

[0008] Furthermore, in step (4), the first-level weighted score is calculated using the current behavior data of the gift giver and the gift receiver, specifically: the first-level weighted score E1 is calculated according to the following formula; E1=(M j *λ j ) / (T i *λ i + M j *λ j ); where subscript i represents the gift giving type, subscript j represents the gift receiving type, and λ i represents the weight of gift type i, λ j represents the weight of gift type j; T i Indicates the score value of gift type i, M j Indicates the score values ​​for gift receiving type j. They are all constants and can be set as needed.

[0009] Furthermore, in step (1), the historical behavior data includes the number of gift giving, gift amount, gift giving frequency and gift type distribution.

[0010] Furthermore, in step (6), the secondary weighted score is calculated using the historical behavior data of the gift giver, specifically: the secondary weighted score E2 is calculated according to the following formula; E2=Q t *λ Q +P t *λ P +D t *λ D +F t *λ F ; Among them, Q t represents the number of gift giving within a certain period of time t, P t represents the gift amount within a certain period of time t, D t In represents the gift-giving frequency in a certain period of time t, F t The score value representing the distribution of gift types within a certain period of time t; Q , P , D and λ F Both represent weights, are constants, and λ Q +λ P +λ D +λ F =1.

[0011] Furthermore, in step (4), when a user gives a virtual gift on the platform, it is first determined whether the current virtual gift is a random gift with multiple special effects.

[0012] The present invention also discloses and protects a chat room platform, including a background server, which stores a computer-readable program for executing any of the random special effect calling methods described above.

[0013] Compared with the prior art, the present invention has the following beneficial effects: Through the present invention, users can trigger additional random special effects with probability by giving virtual gifts in the chat room platform, which increases the entertainment of the platform and helps to improve the competitiveness of the platform; the random special effect calling method is related to the historical behavior data of the gift giver in the platform, and is related to the current behavior data of the gift giver and the gift receiver, which increases the fun and interactivity of the chat room platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a flow chart of Embodiment 1 of the present invention.

[0015] Figure 2 This is a configuration block diagram of the random special effects library in the present invention.

[0016] Figure 3 This is a flow chart of Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0017] The specific implementation of the present invention is described below with reference to the accompanying drawings. In order to fully understand the present invention, many details are described below, but for those skilled in the art, the present invention can be implemented without these details.

[0018] Embodiment 1 like Figure 1 As shown, a method for calling random special effects based on virtual gift giving includes the following steps: Step (1), the platform pre-configures a random special effect library; the random special effect library includes a plurality of special effect sets, and each special effect set is configured with a primary threshold interval and a random factor threshold interval; each special effect set includes at least one special effect subset, and each special effect subset is configured with a secondary threshold interval, and each special effect subset includes at least one special effect element.

[0019] In a specific embodiment, the random special effect library includes three special effect sets, namely, a type A special effect set, a type B special effect set, and a type C special effect set, and is configured as follows: The first-level threshold interval of the A-type special effect set is (0.2, 0.6], and the random factor threshold interval is (0, 0.2].

[0020] The first-level threshold interval of the B-type special effect set is (0.6, 0.9], and the random factor threshold interval is (0, 0.1].

[0021] The first-level threshold interval of the C-type special effect set is (0.9, 1), and the random factor threshold interval is (0, 0.01].

[0022] Specifically, the special effect set of type A includes four special effect subsets, namely special effect subset A1, special effect subset A2 and special effect subset A3. Among them, the secondary threshold interval of special effect subset A1 is [0, 10), including special effect element a11, special effect element a12 and special effect element a13. The secondary threshold interval of special effect subset A2 is [10, 40), including special effect element a21, special effect element a22 and special effect element a23; the secondary threshold interval of special effect subset A3 is [40, 70], including special effect element a31, special effect element a32 and special effect element a33; the secondary threshold interval of special effect subset A4 is [70, 100], including special effect element a41, special effect element a42, special effect element a43 and so on.

[0023] In addition, the number of special effect elements between the special effect subsets may be different, and the same special effect elements may exist, for example, the special effect subset A3 includes the special effect element a11.

[0024] The structure and configuration of the B-type special effect set and the C-type special effect set are similar to those of the A-type special effect set, and Figure 2It should be noted that various configuration parameters of the random special effects library (such as the first-level threshold interval, the random factor threshold area, the second-level threshold interval, and the special effect elements of each special effect subset, etc.) can be set as needed, and no excessive restrictions are made here.

[0025] Step (2): The platform collects and analyzes the historical behavior data of the user in the past period of time. The period of time t can be set as needed, including but not limited to three days or seven days.

[0026] Preferably, the historical behavior data includes the number of gift giving, gift amount, gift giving frequency and gift type distribution.

[0027] Among them, “gift times” refers to the number of times a user has given gifts in the past period of time t, recorded as Q t "Gift amount" refers to the total amount of gifts given by the user in the past period of time t, recorded as P t “Gift frequency” refers to the frequency of gift giving by the user, which is obtained by (number of gift giving / time t), denoted as D t “Gift type distribution” refers to the type distribution of gifts given by users in the past period of time, denoted as F t .

[0028] Step (3): set a weight for each item of behavior data and calculate the individual weighted score for each item of user behavior data.

[0029] Set the number of gifts to Q t The weight is set to λ Q ; Set the gift amount P t The weight is set to λ P ; Set the gift giving frequency to D t The weight is set to λ D ; The distribution of gift types F t The weight is set to λ F . Q +λ P +λ D +λ F =1,λ Q , P , D and λ F They are all constants and their sizes can be set as needed.

[0030] Step (4), when a user gives a virtual gift on the platform, it is determined whether the current virtual gift is a random gift with multiple special effects. If so, the current behavior data of the gift giver and the gift receiver are collected and analyzed; the first-level weighted score is calculated using the current behavior data of the gift giver and the gift receiver; if not, the process ends, i.e., the random special effects are not triggered.

[0031] Preferably, the current behavior data includes the type of gift giving of the current virtual gift by the gift giver and the type of gift receiving of the current virtual gift by the gift receiver. The first-level weighted score E1 is calculated according to the following formula: E1=(M j *λ j ) / (T i *λ i + M j *λ j ); where subscript i represents the gift giving type, subscript j represents the gift receiving type, and λ i represents the weight of gift type i, λ j represents the weight of gift type j, T i Indicates the score value of gift type i, M j Indicates the score value of gift receiving type j.

[0032] The types of virtual gifts include but are not limited to blind boxes (i.e. the sender does not know what the virtual gift is), rings, type A clothes, digital coins, chat room interface skins, etc. The types of virtual gifts received include but are not limited to rings, type A clothes, digital coins, chat room interface skins, etc., and only when the gift type is a blind box, the gift type and the receiving type of the same virtual gift are inconsistent. The platform needs to set a score value for each gift type and each gift type in advance. The following example illustrates: Table 1. Score table of gift giving and gift receiving types

[0033] Step (5) determines whether the first-level weighted score is within the first-level threshold interval of one of the special effect sets; if not, the process ends, i.e., the random special effect is not triggered; if so, the platform randomly generates a random factor, and the value range of the random factor is [0, 1]; further determines whether the random factor is within the random factor threshold interval of the same special effect set; if so, the special effect set corresponding to the first-level threshold interval is selected; if not, the process ends, i.e., the random special effect is not triggered.

[0034] Step (6): Calculate the secondary weighted score using the historical behavior data of the gift giver.

[0035] Preferably, the secondary weighted score E2 is calculated according to the following formula: E2=Q t *λ Q +P t *λ P +D t *λ D +F t *λ F ; Among them, λ Q +λP +λ D +λ F =1,λ Q , P , D and λ F All of them are constants, and their sizes can be set as needed; Q t represents the number of gift giving within a certain period of time t, P t represents the gift amount within a certain period of time t, D t In represents the gift-giving frequency in a certain period of time t, F t The score value represents the distribution of gift types within a certain period of time t.

[0036] Of course, the platform needs to set corresponding scoring values ​​for the distribution of gift types in advance. The following example illustrates: Taking the first two gift types with the highest scores in Table 1 (blind boxes and type A clothes) as considerations, set the scoring values ​​corresponding to different distribution situations.

[0037] Table 2 Score table of different gift-giving types

[0038] Step (7) determines whether the secondary weighted score is within one of the secondary threshold intervals; if so, the platform selects a special effect set corresponding to the secondary threshold interval from the random special effect library; if not, the process ends, i.e., the random special effect is not triggered.

[0039] Step (8): the platform calls the special effect elements of the special effect set selected in step (7), and displays them to one or more of the gift giver, the gift receiver, and the remaining platform users through the user-side electronic device.

[0040] Through steps (1) to (8) of the random special effect calling method, a specific computing model is constructed for the computer system used by the chat room platform. The chat room platform uses the computing model to call and display the random special effects within the platform, thereby increasing the correlation between the chat room platform and the user's behavior data, and increasing the fun and interactivity of the chat room platform.

[0041] Embodiment 2 like Figure 1 , Figure 2 and Figure 3 As shown, the difference between Example 1 and Example 2 is that: in step (1), no random factor threshold interval is configured for each special effect set; in step (5), it is determined whether the first-level weighted score is within one of the first-level threshold intervals; if so, the platform selects the special effect set corresponding to the first-level threshold interval from the random special effect library; if not, the process ends.

[0042] The present invention also discloses and protects a chat room platform, including a background server, wherein the background server stores a computer-readable program for executing the above-mentioned random special effect calling method.

[0043] It is only a specific implementation method of the present invention, but the design concept of the present invention is not limited to this. Any non-substantial changes to the present invention using this concept shall be deemed as an infringement of the protection scope of the present invention.

Claims

1. A random special effect calling method based on virtual gift giving, characterized in that: The following steps are involved: Step (1), the platform pre-configures a random special effect library; the random special effect library includes a plurality of special effect sets, and each special effect set is configured with a first-level threshold interval; each special effect set includes at least one special effect subset, and each special effect subset is configured with a second-level threshold interval, and each special effect subset includes at least one special effect element; Step (2), the platform collects and analyzes the user's historical behavior data over the past period of time; Step (3), set a weight for each item of behavior data, and calculate the single weighted score of each item of user's behavior data; Step (4), when a user gives a virtual gift on the platform, the current behavior data of the gift giver and the gift receiver are collected and analyzed; the first-level weighted score is calculated using the current behavior data of the gift giver and the gift receiver; Step (5), determining whether the first-level weighted score is within one of the first-level threshold intervals; if so, the platform selects a special effect set corresponding to the first-level threshold interval from the random special effect library; if not, ending; Step (6), using the historical behavior data of the gift giver, calculate the secondary weighted score; Step (7), determining whether the secondary weighted score is within one of the secondary threshold intervals; if so, the platform selects a special effect set corresponding to the secondary threshold interval from the random special effect library; if not, the process ends; Step (8): the platform calls the special effect elements of the special effect set selected in step (7), and displays them to one or more of the gift giver, the gift receiver, and the remaining platform users through the user-side electronic device.

2. A method for calling random special effects based on virtual gift giving according to claim 1, characterized in that: In the step (1), a random factor threshold interval for selecting the special effect set is also configured for each special effect set; The step (5) is replaced by the following content: determine whether the first-level weighted score is within the first-level threshold interval of one of the special effect sets; if not, end; if so, the platform randomly generates a random factor; further determine whether the random factor is within the random factor threshold interval of the same special effect set; if so, select the special effect set corresponding to the first-level threshold interval; if not, end.

3. A random special effect calling method based on virtual gift giving according to claim 1, characterized in that: In the step (4), the current behavior data includes the gift type of the current virtual gift at the gift sender and the gift type of the current virtual gift at the gift receiver.

4. A method for calling random special effects based on virtual gift giving according to claim 3, characterized in that: In the step (4), the first-level weighted score is calculated using the current behavior data of the gift giver and the gift receiver. Specifically, the first-level weighted score E1 is calculated according to the following formula; E1=(M j *λ j ) / (T i *λ i + M j *λ j ); where subscript i represents the gift giving type, subscript j represents the gift receiving type, and λ i represents the weight of gift type i, λ j represents the weight of gift type j, T i Indicates the score value of gift type i, M j Indicates the score value of gift receiving type j.

5. A random special effect calling method based on virtual gift giving according to claim 1, characterized in that: In step (1), the historical behavior data includes the number of gift giving, gift amount, gift giving frequency and gift type distribution.

6. A method for calling random special effects based on virtual gift giving according to claim 5, characterized in that: In the step (6), the secondary weighted score is calculated using the historical behavior data of the gift giver, specifically: the secondary weighted score E2 is calculated according to the following formula; E2=Q t *λ Q +P t *λ P +D t *λ D +F t *λ F ; Among them, Q t represents the number of gift giving within a certain period of time t, P t represents the gift amount within a certain period of time t, D t In represents the gift-giving frequency in a certain period of time t, F t In the score value representing the distribution of gift types within a certain period of time t, λ Q , P , D and λ F Both represent weights, are constants, and λ Q +λ P +λ D +λ F =1.

7. A random special effect calling method based on virtual gift giving according to claim 1, characterized in that: In step (4), when a user gives a virtual gift on the platform, it is first determined whether the current virtual gift is a random gift with multiple special effects.

8. A chat room platform, including a backend server, characterized in that: The background server stores a computer-readable program for executing the random special effect calling method as described in any one of claims 1-7.

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