Object recommendation system, object recommendation program, and object recommendation method

Abstract

Add objects that do not diminish the enjoyment of the electronic game. [Solution] The object recommendation system is characterized by identifying and proposing to the user objects that the user does not own but which are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns.

Description

Technical Field

[0001] The present invention relates to an object recommendation system, an object recommendation program, and an object recommendation method.

Background Art

[0002] There is an electronic game that determines the outcome of a battle game that constitutes a deck by using a deck that combines objects that are game elements such as virtual cards. Further, in such an electronic game, there is a system that gives a player an object that can be used in the game by lottery.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] When giving a player an object that can be used in an electronic game, it is preferable that the object be one that can maintain the player's interest in the electronic game. That is, if the object to be given is not effective in the electronic game, the interest of the electronic game may be lost.

[0005] One of the problems of the present invention is to provide an object recommendation system, an object recommendation program, and an object recommendation method that can give an object that does not lose the interest in an electronic game.

Means for Solving the Problems

[0006] One aspect of the present invention is an object recommendation system characterized by identifying and proposing to the user objects that the user does not own and that are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns.

[0007] In this case, if the recommended object is available, it is preferable to present the user with information indicating that the recommended object is available.

[0008] Furthermore, if the user is using multiple decks, it is preferable to identify the recommended objects for each of those decks and propose them to the user.

[0009] Furthermore, it is preferable that the display of the suggested object to the user can be switched on or off.

[0010] Another aspect of the present invention is an object recommendation program characterized by causing a computer to function in such a way that, based on the objects contained in the deck being used by the user and the objects owned by the user, it identifies and proposes to the user as recommended objects objects that the user does not own and that are recommended for use in the deck.

[0011] Another aspect of the present invention is an object recommendation method characterized by causing a computer to perform a process that identifies objects not owned by the user but recommended for use in the deck, based on the objects included in the deck being used by the user and the objects owned by the user, and proposes these objects to the user as recommended objects. [Effects of the Invention]

[0012] According to the present invention, it is possible to provide an object recommendation system, an object recommendation program, and an object recommendation method that can assign objects in electronic games without compromising their entertainment value. Other objects of embodiments of the present invention will become apparent by referring to the entire specification. [Brief explanation of the drawing]

[0013] [Figure 1] This figure shows the configuration of an electronic game information processing system according to an embodiment of the present invention. [Figure 2] This figure shows the server configuration in an embodiment of the present invention. [Figure 3] This figure shows the configuration of the client in an embodiment of the present invention. [Figure 4] This figure shows an example of an object database in an embodiment of the present invention. [Figure 5] This figure shows an example of a player database in an embodiment of the present invention. [Figure 6] This figure shows an example of the display of the deck screen in an embodiment of the present invention. [Figure 7] This figure shows an example of a deck database in an embodiment of the present invention. [Figure 8] This figure shows an example of the display of the battle screen in an embodiment of the present invention. [Figure 9] This figure shows an example of a match log database in an embodiment of the present invention. [Figure 10] This figure shows an example of a deck win / loss database in an embodiment of the present invention. [Figure 11] This figure shows an example of an object pair score database in an embodiment of the present invention. [Figure 12] This diagram illustrates the process for determining the recommended object according to this embodiment. [Figure 13] This diagram illustrates the process of calculating a total score by adding scores for each type of recommended candidate piece in an embodiment of the present invention. [Figure 14]It is a diagram showing an example of a lottery database in an embodiment of the present invention. [Figure 15] It is a diagram for explaining a process for determining a recommended object according to this embodiment. [Figure 16] It is a diagram showing an example of the display of a lottery home screen in an embodiment of the present invention. [Figure 17] It is a diagram showing an example of the display of an explanation screen regarding object recommendation in an embodiment of the present invention. [Figure 18] It is a diagram showing an example of the display of an explanation screen regarding object recommendation in an embodiment of the present invention. [Figure 19] It is a diagram showing an example of the display of an explanation screen regarding object recommendation in an embodiment of the present invention. [Figure 20] It is a diagram showing an example of the display of a lottery home screen in an embodiment of the present invention. [Figure 21] It is a diagram showing an example of the display of a piece details screen in an embodiment of the present invention. [Figure 22] It is a diagram showing an example of the display of a deck details screen in an embodiment of the present invention. [Figure 23] It is a diagram showing an example of the display of a lottery home screen in an embodiment of the present invention.

Mode for Carrying Out the Invention

[0014] [System Configuration] As shown in FIG. 1, an electronic game information processing system 100 in an embodiment of the present invention includes a server 102 and a client 104. The client 104 may be singular or plural. The server 102 and the client 104 are connected to each other via an information communication network 106 such as the Internet so as to be able to exchange information.

[0015] The information and communication network 106 is not limited to the Internet, but can be any network that enables communication between the server 102 and the client 104. For example, it may be a dedicated line, a public line (telephone line, mobile communication line, etc.), a wired LAN (Local Area Network), a wireless LAN, or a combination of the Internet and these.

[0016] As shown in Figure 2, the server 102 is composed of a processing unit 10, a storage unit 12, an input unit 14, an output unit 16, and a communication unit 18. The processing unit 10 includes means for performing arithmetic processing such as a CPU. The processing unit 10 provides electronic game functions to the client 104 in the electronic game information processing system 100 of this embodiment by executing the electronic game information processing server program stored in the storage unit 12. It also implements functions for recommending and assigning electronic objects by executing the object recommendation server program. The storage unit 12 includes storage means such as semiconductor memory or a memory card. The storage unit 12 is connected to the processing unit 10 in an accessible manner and stores the electronic game information processing server program, the object recommendation server program, and information necessary for their processing. The input unit 14 includes means for inputting information. The input unit 14 includes, for example, a keyboard, touch panel, buttons, etc., for receiving input from an administrator. The output unit 16 includes means for outputting the processing results of the server 102, such as a user interface screen (UI) for receiving input information from an administrator. The output unit 16 includes, for example, a display for presenting images to an administrator. The communication unit 18 is configured to include an interface for communicating information with the client 104 via the information and communication network 106. The communication by the communication unit 18 may be wired or wireless.

[0017] Server 102 receives access from each user's client 104 via the information and communication network 106 to receive electronic game information processing services, stores and manages information about each user in a storage device such as a database, and provides services to each user via the information and communication network 106.

[0018] As shown in Figure 3, client 104 is composed of a processing unit 20, a storage unit 22, an input unit 24, an output unit 26, and a communication unit 28. Client 104 is also referred to as a communication terminal. The processing unit 20 includes means for performing arithmetic processing such as a CPU. The processing unit 20 realizes the function of a client terminal in the electronic game information processing system 100 in this embodiment by executing the electronic game information processing client program stored in the storage unit 22. The processing unit 20 also realizes the function of a client terminal in the object recommendation system in this embodiment by executing the object recommendation client program stored in the storage unit 22. The storage unit 22 includes storage means such as semiconductor memory or a memory card. The storage unit 22 is connected to the processing unit 20 in an accessible manner and stores the electronic game information processing client program, the object recommendation client program, and information necessary for their processing. The input unit 24 includes means for inputting information. The input unit 24 includes, for example, a keyboard, touch panel, buttons, motion sensor, etc., for receiving input from the user. The output unit 26 includes means for outputting information necessary for processing on the client 104, such as a display that shows image information such as a screen for receiving input information from the user or a user interface screen (UI). The communication unit 28 is configured to include an interface for communicating information with the server 102 via the information communication network 106. Communication by the communication unit 28 can be wired or wireless.

[0019] Client 104 can be any information processing device capable of executing a client program for providing electronic game information processing services. For example, Client 104 can be a stationary or portable game console, a personal computer (PC), a tablet computer, a smartphone, a mobile phone terminal, a PHS (Personal Handy-phone System) terminal, a personal digital assistant (PDA), or a multi-functional television receiver with information processing capabilities (so-called smart TV).

[0020] [Overview of Electronic Game Services] In this embodiment, a competitive electronic game in which two players compete using their respective clients 104 will be described as an example.

[0021] Each player plays the electronic game using electronic objects called pieces (hereinafter simply referred to as "objects"). Each piece is assigned a character. Each character is assigned attributes such as hit points, skills, and attack power.

[0022] Figure 4 shows an example of an object database that stores information about game pieces in an associated manner. The object database stores the object ID, object name, object rarity, hit points (HP), skill, attack power, and cost, all uniquely assigned to each object.

[0023] Here, the cost of an object is a value considered when constructing a deck, as will be described later. It is preferable to set the cost of an object so that the higher its value in the electronic game, the higher its cost. For example, it is preferable to set the cost of an object so that the higher its hit points (HP), the higher its cost. Also, for example, it is preferable to set the cost of an object so that the higher its skill value in the electronic game, the higher its cost. Also, for example, it is preferable to set the cost of an object so that the higher its attack power, the higher its cost. Furthermore, it is preferable to combine these factors so that the cost of an object so that the higher its value in the electronic game, the higher its cost.

[0024] Furthermore, the electronic object is not limited to a game piece, but can be any form that can be treated as an electronic medium to which the present invention can be applied. The object may also be used for other purposes, such as electronic games.

[0025] The method of acquiring objects is not particularly limited. Objects may be acquired, for example, through a lottery known as a gacha (registered trademark). The lottery may be conducted for a fee, such as when the user pays some kind of compensation. Alternatively, the lottery may be conducted for free. Furthermore, the lottery may be conducted in an electronic game when certain conditions are met.

[0026] Objects may be acquired by users free of charge as a reward, or they may be acquired by users for a fee, such as by paying a fee. For example, objects may be available for purchase in an online shop. Alternatively, objects may be granted upon joining a fan club. Alternatively, objects may be granted upon participating in an event on a designated social networking service. Alternatively, objects may be provided or rented from other users or systems. However, the method of acquiring objects is not limited to these methods, and any method of acquisition is acceptable.

[0027] Figure 5 shows an example of a player database that stores information about the user who will be playing the game. The player database stores the user ID, username, billing information, information about the objects owned by the user, the cost limit, the user's rank, and the number of coins owned, all linked together.

[0028] The User ID is a unique identifier assigned to each user who becomes a player. The billing information is information used when billing is performed in the electronic game information processing system 100. The billing information is not particularly limited, but can include, for example, a credit card number, a bank account number, or electronic money account information. The object information owned by the user is the object ID of the object owned by each user. In this embodiment, the object information stores the object ID that identifies the piece owned by each user. The cost limit is the upper limit of the cost of pieces that can be included in a deck when constructing a piece deck, as described later. The user rank is the user's rank in the electronic game. The rank is determined, for example, based on past wins and losses in the electronic game. Coins are virtual currency used in the electronic game information processing system 100. Coins are consumed when processing is performed in the electronic game information processing system 100. Coins are consumed, for example, when performing a lottery to acquire an object, as described later. It is preferable that coins can be purchased by the user through billing.

[0029] Furthermore, a gift box may be provided for each user, allowing them to store their pieces in it. In this case, the player database stores an object ID that identifies the pieces stored in the gift box, associating it with the user. Pieces stored in the gift box may be made available for the user to retrieve and use as needed. In this embodiment, however, pieces stored in the gift box are not treated as pieces owned by the user during processing.

[0030] In the competitive electronic game of this embodiment, each user plays using the pieces they own. Players select a predetermined number of pieces from their owned pieces to form a deck, and then play the electronic game using the pieces in their deck. As a player, the user selects pieces to form a deck that gives them an advantage in the competitive electronic game.

[0031] In this case, when constructing a deck, it is preferable to set a condition that the total cost of the pieces included in the deck must be less than or equal to the player's (user's) cost limit. It is preferable that the cost limit differs for each user rank. For example, it is preferable that the higher the user's rank, the higher their cost limit should be. This allows users in electronic games to include more expensive pieces (objects) or more pieces (objects) in their decks as their rank increases.

[0032] Decks may allow the designation of a leader piece. Only one leader piece can be designated per deck. If a piece has a leader piece skill, that skill can be used by designating it as the leader piece in the deck.

[0033] Figure 6 shows an example of a deck screen 200 that represents the contents of a constructed deck. The deck screen 200 consists of a player name display area 202, a cost display area 204, a hit point display area 206, an attack power display area 208, and an object display area 210. The player name display area 202 displays the name of the player (user). The cost display area 204 displays the total cost of the pieces included in the deck and the maximum cost limit for the player (user). In Figure 6, the total cost of the pieces included in the deck is 185, and the maximum cost limit for the player (user) is 200. The hit point display area 206 displays the total hit points (HP) of the pieces that make up the deck. The attack power display area 208 displays the total attack power (ATK) of the pieces that make up the deck.

[0034] The object display area 210 displays images representing the pieces (objects) that make up the deck. These images can be prepared in advance by having image data ready for each piece (object), and the images can be displayed based on that image data. In the deck screen 200 of this embodiment, one deck is made up of 16 pieces, and the images of the 16 pieces are displayed as the objects that make up the deck.

[0035] The process for selecting pieces to make up a deck is not particularly limited; it is sufficient for the user, as a player, to select pieces from those they own and include them in the deck. The data for the pieces that make up the deck is stored in a deck database, as shown in Figure 7. The deck database stores the user ID of the player and the object ID of the pieces that make up the deck, associated with each other. The deck database may also store the object IDs of pieces that have already been used in the electronic game as used pieces.

[0036] In this embodiment, the Othello game is described as an example of a competitive electronic game. In the Othello game, each of the two players who are opponents is assigned either black or white pieces. Players use the pieces that make up their deck as their assigned black or white pieces and take turns placing these pieces on the board. The game progresses when black pieces surround one or more white pieces vertically, horizontally, or diagonally on the board, changing the surrounded white pieces to black, or when white pieces surround one or more black pieces vertically, horizontally, or diagonally, changing the surrounded black pieces to white. When a player places a piece on the board and a piece on the board is changed from black to white or from white to black, the total hit points of the opponent player are reduced according to the hit points of the changed piece and the attack power of the pieces involved in the change. The electronic game progresses as the players take turns placing pieces on the board, and the player who reaches the total hit points of either player wins.

[0037] Each player can use a predetermined number of pieces selected from the unused pieces that make up the deck. In this embodiment, four pieces are randomly selected. Players play the electronic game by selecting appropriate pieces from the selected pieces and placing them on the board. When a piece is used, a new piece is randomly selected from the unused pieces that make up the deck and replaced. In addition, an object ID is stored in the deck database as the used piece associated with the player.

[0038] Figure 8 shows an example of the display of the Othello game screen 300. The Othello game screen 300 consists of a player name display area 302, an opponent player hit point display area 304, an opponent player name display area 306, a board display area 308, a hit point display area 310, and a piece display area 312.

[0039] The player name display area 302 displays the username of the player. The opponent player hit point display area 304 displays information about the opponent player's hit points. The opponent player hit point display area 304 displays the current hit points and the total hit points of the pieces included in the deck. In Figure 8, the current hit points are 9500 and the total hit points of the pieces included in the deck are 13290. Alternatively, the opponent player hit point display area 304 may display the ratio of the current hit points to the total hit points of the pieces included in the deck as a bar graph. The opponent player name display area 306 displays the username of the opponent player. The opponent player name display area 306 displays the game board, which is the arena for the electronic game. The hit point display area 310 displays the player's current hit points and the total hit points of the pieces included in the deck. In Figure 8, the current hit points are 13520 and the total hit points of the pieces included in the deck are 18630. Furthermore, the hit point display area 310 may display the ratio of the current hit point value to the total hit point value of the pieces included in the deck as a bar graph. The piece display area 312 displays information about the pieces that each player can use. As described above, a predetermined number of unused pieces from the pieces that make up the deck are selected and displayed in the piece display area 312.

[0040] [Recommended actions for objects] <Recommended processing based on the piece> The electronic game information processing system 100 also functions as an object recommendation system by performing the following processes. In this embodiment, the object recommendation system is described as a part of the electronic game information processing system 100, but it may be a separate system from the electronic game information processing system 100.

[0041] The piece-based object recommendation process in this embodiment will be explained below with specific examples. In the piece-based object recommendation process, a process is performed to recommend pieces that are considered effective in the game based on the pieces owned by the user and used in their deck.

[0042] In this example, for simplicity, we will assume there are 26 types of pieces (objects), and each deck is composed of three pieces. Additionally, pieces may have skills assigned to them.

[0043] Figure 9 shows an example of a match log database that stores the details of past matches in an electronic game. The match log database includes information such as the user ID, the pieces that make up the deck, the opponent's user ID, and the win / loss result. The win / loss result is stored with 1 for a win and 0 for a loss. The match log database is updated each time a match is played in the electronic game.

[0044] Figure 10 shows the deck win / loss database generated based on the match log database. The deck win / loss database includes the user ID, the pieces that make up the deck, and the win rate. The win rate is calculated by dividing the number of wins by the total number of matches for each combination of user ID and pieces that make up the deck. The deck win / loss database is updated each time a match is played in the electronic game.

[0045] The win rate may be the win rate aggregated over the entire period, or the win rate aggregated for a specific period (for example, 30 days, 60 days, 90 days, etc., as appropriate). Furthermore, the win rate may be the win rate aggregated for all users, or the win rate aggregated for a specific group of users (for example, for each class of users, such as D-tier or A-tier). The frequency of updating the deck win / loss database may be set to regular intervals (for example, daily, weekly, etc., as appropriate). Note that class is an index that ranks users according to the results of each event and match (season matches, etc.). Class rankings can be A-tier, B-tier, C-tier, D-tier, etc., from best to worst user.

[0046] Figure 11 shows an example of an object pair score database. The object pair score database is a database that lists the combinations of pieces included in a deck and scores the recommendation level of the second piece relative to the first piece. Here, the score is the win rate for each combination of the first and second pieces. For example, in Figure 10, the combination of piece A and piece B is used only in the deck of user ID U01, and the win rate of that deck is 0.7, so the win rates for the combination of piece A and piece B and piece A are 0.7. Also, the combination of piece B and piece C is used in the decks of users U01, U02, and U03, and the win rates of those decks are 0.7, 0.3, and 0.5 respectively, so the win rates for the combination of piece B and piece C and piece C and piece B are the average of these, 0.5 (=(0.7+0.3+0.5) / 3). Similarly, the win rates for other piece combinations are calculated and stored in association with them.

[0047] Alternatively, the score may be multiplied by a coefficient representing the likelihood of using the first and second pieces. For example, by referring to a match log database like the one shown in Figure 9, the score may be multiplied by the value obtained by dividing the number of matches played with decks containing both the first and second pieces by the number of matches played with decks containing only the first piece. In this case, the likelihood of use may be aggregated across all users, or it may be aggregated for specific user groups (for example, by user class such as D-tier or A-tier). Furthermore, the likelihood of use may be aggregated over the entire period, or only for a specific period (for example, the last 60 days).

[0048] The object recommendation process uses an object pair score database to determine the recommended objects (hereinafter referred to as "recommended objects") for the decks used by each user. If a user uses multiple decks, recommended objects may be determined for each of those decks. Alternatively, recommended objects may be determined for the deck the user has used most recently. Furthermore, recommended objects may be determined for the deck the user used in a given event. Finally, recommended objects may be determined for the deck the user uses most frequently.

[0049] Figure 12 illustrates the process for determining recommended objects. It shows the process for determining recommended objects for decks used by users with user IDs U01 and U20. Note that each user is assumed to own no objects other than the pieces that make up their deck.

[0050] As shown in Figure 12, each piece that makes up the deck used by each user is treated as a target piece, and the object pair score database is referenced to identify the piece associated with the target piece as the second piece when the target piece is treated as the first piece. Scores are then extracted for combinations of the target piece and the recommended candidate piece. If a piece that each user already owns (in this case, a piece that makes up the deck) is a recommended candidate piece, it is excluded from the list of recommended candidates.

[0051] For example, the deck used by user ID U01 consists of pieces A, B, and C. Referring to the object pair score database shown in Figure 11, if piece A, which makes up the deck, is selected as the target piece, then pieces B and C, which are associated with piece A as the first piece and second pieces, are selected as recommended candidate pieces. Then, a score of 0.7 is extracted for the combination of piece A and piece B, and a score of 0.7 is extracted for the combination of piece A and piece C. Similarly, if piece B, which makes up the deck, is selected as the target piece, then pieces A, C, D, and E are selected as recommended candidate pieces, and scores of 0.7, 0.5, 0.3, and 0.5 are extracted for each combination. Also, similarly, if piece C, which makes up the deck, is selected as the target piece, then pieces A, B, D, and E are selected as recommended candidate pieces, and scores of 0.7, 0.5, 0.3, and 0.5 are extracted for each combination. Then, pieces that the user already owns, namely pieces A, B, and C that make up the deck, are excluded from the list of recommended pieces (see the shaded cells in Figure 12).

[0052] Furthermore, the deck used by the user with user ID U20 consists of pieces A, C, and D. Referring to the object pair score database shown in Figure 11, if piece A, which makes up the deck, is selected as the target piece, pieces B and C, which are associated with piece A as the first piece and second pieces, are selected as recommended candidate pieces. Then, a score of 0.7 is extracted for the combination of piece A and piece B, and a score of 0.7 is extracted for the combination of piece A and piece C. Similarly, if piece C, which makes up the deck, is selected as the target piece, pieces A, B, D, and E are selected as recommended candidate pieces, and scores of 0.7, 0.5, 0.3, and 0.5 are extracted for each combination. Similarly, if piece D, which makes up the deck, is selected as the target piece, pieces B and C are selected as recommended candidate pieces, and scores of 0.3 and 0.3 are extracted for each combination. Then, pieces that the user already owns, i.e., pieces A, C, and D that make up the deck, are excluded from the recommended candidate pieces (see shaded cells in Figure 12).

[0053] Next, the system performs a process to sum the scores of the recommended pieces for each deck used by the user. The score is then added for each type of recommended piece extracted in the above process to calculate the total score. Figure 13 shows an example of calculating the total score by adding the scores for each type of recommended piece. Note that before the score summing process, the score of leader pieces in a deck may be increased. For example, the score of leader pieces in a deck may be multiplied by 5.

[0054] For example, for a deck used by a user with user ID U01, the recommended pieces are pieces D and E. In the process shown in Figure 12, the score of 0.3 extracted for the combination of piece D with piece B and the score of 0.3 extracted for the combination of piece C are added together to calculate a total score of 0.6. Similarly, in the process shown in Figure 12, the score of 0.5 extracted for the combination of piece E with piece B and the score of 0.5 extracted for the combination of piece C are added together to calculate a total score of 1.0.

[0055] Furthermore, for a deck used by a user with user ID U20, the recommended pieces are pieces B and E. Therefore, in the process shown in Figure 12, the score extracted for piece B in combination with piece A (0.7), the score extracted for combination with piece C (0.5), and the score extracted for combination with piece D (0.3) are added together to calculate a total score of 1.5. Similarly, in the process shown in Figure 12, the score extracted for piece E in combination with piece C (0.5) is used to calculate a total score of 0.5.

[0056] Furthermore, the probability of acquiring a recommended object should be considered in the means of acquiring the object. For example, if the means of acquiring pieces is a lottery (e.g., gacha), the probability of acquiring an object may differ depending on the type of lottery (type of gacha). Therefore, it is preferable to determine the recommended object by considering the relevant probability for each type of lottery.

[0057] Figure 14 shows an example of a lottery database that combines a lottery ID indicating the type of lottery with the probability of a piece being drawn in that lottery (= the probability of acquiring a piece in that lottery). For example, in a lottery with lottery ID L01, the probability of piece D being drawn is 90%, and the probability of piece E being drawn is 10%. Also, in a lottery with lottery ID L02, the probability of piece B being drawn is 80%, and the probability of piece E being drawn is 20%.

[0058] The final score for each recommended candidate piece is calculated by multiplying the total score calculated for that piece by the probability of that piece being drawn (the probability of acquiring that piece). Figure 15 illustrates this process.

[0059] For example, for pieces D and E, which are recommended candidate pieces for a deck used by a user with user ID U01, the final score is calculated by multiplying the total score by the probability of obtaining each piece in a draw in which that piece can be obtained. For piece D, which has a total score of 0.6, it has a 90% chance of being obtained in a draw with draw ID L01, so the final score is calculated by multiplying the total score of 0.6 by the drop rate (acquisition rate) of 90%, resulting in a final score of 0.54. For piece E, which has a total score of 1.0, it has a 10% chance of being obtained in a draw with draw ID L01, so the final score for the draw with draw ID L01 is calculated by multiplying the total score of 1.0 by the drop rate (acquisition rate) of 10%, resulting in a final score of 0.10. Furthermore, piece E, which has a total score of 1.0, has a 20% chance of being drawn (obtained) in the draw with draw ID L02. Therefore, the final score for the draw with draw ID L02 is calculated by multiplying the total score of 1.0 by the draw rate (acquisition rate) of 20%, resulting in a final score of 0.20.

[0060] From the final scores calculated in this way, the combination of the piece with the highest final score and the draw is selected, and that piece is designated as the recommended object. For the deck used by the user with user ID U01, piece D is selected as the recommended object, and piece D will be recommended in the draw where the draw ID L01 has a chance of producing piece D (see the unshaded cell in Figure 15).

[0061] Furthermore, for example, for pieces B and E, which are recommended candidate pieces for a deck used by a user with user ID U20, the final score is calculated by multiplying the total score by the probability of obtaining each piece in a draw in which that piece can be obtained. For piece B, which has a total score of 1.5, it has an 80% chance of being obtained in a draw with draw ID L02, so the final score is calculated by multiplying the total score of 1.5 by the draw rate (acquisition rate) of 80%, resulting in a final score of 1.20. For piece E, which has a total score of 0.5, it has a 10% chance of being obtained in a draw with draw ID L01, so the final score for a draw with draw ID L01 is calculated by multiplying the total score of 0.5 by the draw rate (acquisition rate) of 10%, resulting in a final score of 0.05. Furthermore, piece E, which has a total score of 0.5, has a 20% chance of being drawn (obtained) in the draw with draw ID L02. Therefore, the final score for the draw with draw ID L02 is calculated by multiplying the total score of 0.5 by the draw rate (acquisition rate) of 20%, resulting in a final score of 0.10.

[0062] From the final scores calculated in this way, the combination of the piece with the highest final score and the draw is selected, and that piece is designated as the recommended object. For the deck used by the user with user ID U20, piece B is selected as the recommended object, and piece B will be recommended in the draw where the draw ID L02 has a chance of producing piece B (see the unshaded cell in Figure 15).

[0063] In this embodiment, a filter was applied to exclude pieces already owned by the user from the list of recommended pieces, but the filtering process is not limited to this.

[0064] For example, a filter may be applied to exclude pieces from the list of recommended pieces based on the skills assigned to them. For instance, if adding a piece to a deck a user is using would cause the effects of skills originally active in that deck to stop working, or if the effects of the skills of the added piece would not work, that piece may be excluded from the list of recommended pieces.

[0065] Furthermore, for example, if there are combinations of pieces that cannot be used simultaneously in a single deck, pieces that cannot be added to the deck the user is using may be excluded from the list of recommended pieces.

[0066] Furthermore, in this embodiment, the probability of acquiring an object in a means of acquiring an object, such as a lottery, was considered, but the recommended object may be determined without considering this. For example, as shown in Figure 15, a total score indicating the win rate may be calculated for each recommended candidate piece, and the recommended object may be determined according to that total score. In this case, the final score can be calculated by multiplying the total score indicating the win rate by the probability that the piece will be drawn in a lottery in which there is a possibility of drawing (acquiring) that piece (the probability of acquiring that piece).

[0067] Furthermore, the final score may be calculated by considering when the recommended candidate pieces were released. For example, it is preferable to calculate the final score by multiplying the total score by a coefficient that is higher the closer the recommended candidate piece was released to the present time. This increases the likelihood that pieces released closer to the present time will be selected as recommended objects.

[0068] Furthermore, if a single user is using multiple decks, recommended objects may be determined for each of those decks, and recommended objects may be suggested for each deck. Alternatively, recommended objects may be determined for each of those decks, and the recommended object with the highest final score may be selected. For example, if a single user is using a different deck for each event in an electronic game, the recommended deck and recommended objects may be combined and recommended for that event.

[0069] Through the object recommendation process described above, it is possible to determine which pieces, when added to the user's deck, will increase their win rate as recommended objects. Furthermore, by considering the probability of acquiring such pieces through means such as drawing lots, it is possible to determine which pieces have a high probability of being acquired as recommended objects.

[0070] In this embodiment, each deck is described as consisting of three pieces, but the same process can be applied even if the number of pieces in each deck increases.

[0071] <Community Recommended Processing> The community-based object recommendation process in this embodiment will be described below with specific examples. In the community-based object recommendation process, popular raffles among multiple users are selected as the target for recommendation.

[0072] Specifically, the system determines which type of lottery (e.g., the type of gacha (registered trademark)) has been most frequently used by all users over a predetermined period in the past, and this will be selected as the recommended type. The predetermined period can be set as appropriate, for example, one week, one month, etc.

[0073] Furthermore, instead of targeting all users, the system may recommend the type of lottery (e.g., the type of gacha) that has been most frequently used for object lottery processing in a predetermined period of time, targeting users who meet specific conditions. The specific condition could be, for example, belonging to the same class as the user for whom the recommendation is presented. In this case, the type of lottery (e.g., the type of gacha) that has been most frequently used for object lottery processing in a predetermined period of time will be recommended for all users belonging to the same class as the user for whom the recommendation is presented. Another specific condition could be, for example, the user belonging to a higher class. In this case, the type of lottery (e.g., the type of gacha) that has been most frequently used for object lottery processing in a predetermined period of time will be recommended for all users belonging to that higher class. The class level considered a higher class can be set as appropriate. Another specific condition could be that the win rate is above a certain threshold during a predetermined period. In this case, the type of lottery (e.g., the type of gacha) that has been most frequently used for object lottery processing in a predetermined period will be recommended for all users whose win rate is above the threshold during that period.

[0074] The specific conditions are not limited to these and may be set as appropriate. In other words, users of the electronic game information processing system 100 can be classified into categories, and the type of lottery in which object lottery processing was performed most frequently by users belonging to that category can be determined as the recommended type.

[0075] [Presentation of recommendations] The following describes the process of presenting the user with the pieces (objects) that have been determined to be recommended in the object recommendation process described above, and the type of lottery (e.g., the type of gacha (registered trademark)) used to acquire them. In the following process, the information necessary for display will be sent from server 102 to client 104 as appropriate, by referring to the databases mentioned above.

[0076] Figure 16 shows an example of the display of the lottery home screen 400 that is shown to client 104 when a lottery is held to acquire an object. The lottery home screen 400 consists of a username display area 402, a user information display area 404, a coin display area 406, a lottery information setting area 408, a coin purchase button 410, a piece box expansion button 412, a lottery image display area 414, a single draw button 416, a multiple draw button 418, a featured piece display area 420, a piece box selection button 422a, a shop selection button 422b, a match selection button 422c, a lottery selection button 422d, and a menu selection button 422e. The lottery home screen 400 can be displayed by selecting the lottery selection button 422d.

[0077] A separate lottery home screen 400 is prepared for each type of lottery. If there are multiple types of lotteries that the user can perform, the user can switch between the lottery home screens 400 provided for each type of lottery by scrolling the lottery home screen 400 displayed on the output unit 26 of the client 104 up and down. When performing a lottery for pieces (objects), the lottery is performed with the lottery home screen 400 for that lottery displayed.

[0078] The username display area 402 is an area that displays the username of a user who plays the electronic game using the client 104. The user information display area 404 is an area that displays information about the user. For example, the user information display area 404 displays information stored in the player database. The coin display area 406 is an area that displays the remaining number of coins currently held by the user. The lottery information setting area 408 is an area that displays information that identifies the type of lottery (for example, the type of Gacha) currently displayed on the output unit 26 of the client 104. The lottery information setting area 408 may also display the object recommendation setting switch 408a and the help button 408b. The object recommendation setting switch 408a is a switch that sets whether or not to present the user with the piece (object) that has been determined to be a recommended target and the type of lottery (for example, the type of Gacha) to acquire it. In other words, if the object recommendation setting switch 408a is set to ON, the user will be presented with the pieces (objects) that have been determined to be recommended and the type of lottery (e.g., the type of Gacha (registered trademark)) to acquire them. Conversely, if the object recommendation setting switch 408a is set to OFF, the user will not be presented with the pieces (objects) that have been determined to be recommended and the type of lottery (e.g., the type of Gacha (registered trademark)) to acquire them. Alternatively, the object recommendation setting switch 408a may not be displayed on the lottery home screen 400, but rather on a separate menu screen (not shown) displayed by the menu selection button 422e, allowing the user to set it to ON / OFF.

[0079] The Help button 408b is a button that displays a screen explaining that the lottery support function, i.e., the object recommendation function, is available when selected. When the user selects (clicks or taps) the Help button 408b, the explanation screen 500 about object recommendation is displayed, as shown in Figure 17. The explanation screen 500 displays an explanation display area 502, a back button 504a, a forward button 504b, and an OK button 504c.

[0080] The explanation display area 502 is an area for displaying explanations of the object recommendation function. The back button 504a is a button to select (click or tap) to return to the previous display content of the explanation screen 500. The forward button 504b is a button to select (click or tap) to advance to the next display content of the explanation screen 500. The OK button 504c is a button to select (click or tap) to return to the screen before transitioning to the explanation screen 500.

[0081] The explanatory display area 502 may contain, for example, "(Functional description) The deck you are currently using..." It is preferable to display an explanation of the general object recommendation functions, such as a support function that notifies users of a lottery that will dispense recommended pieces. Additionally, explanations of other important notes may be displayed.

[0082] Furthermore, by selecting the forward button 504b, an explanation of object recommendations based on the piece-based recommendation process may be displayed. For example, as shown in Figure 18, it is preferable to display an explanation of the function that recommends objects and draws based on the piece-based recommendation process, such as "(Draw Support Function) We will suggest recommended pieces for the deck you have been using most recently. Change and display." In addition, explanations of other precautions may be displayed. At this time, as shown in specific display example 502a, an example of how objects and draws are recommended on the draw home screen 400 may be shown.

[0083] Furthermore, by selecting the forward button 504b, an explanation of object recommendations based on community-based recommendation processing may be displayed. For example, as shown in Figure 19, it is preferable to display an explanation of the function for which lotteries are recommended based on community-based recommendation processing, such as "(Lottery Support Function) We will notify you of lotteries that are popular with users," in the explanation display area 502. In addition, explanations of other precautions may be displayed. At this time, as shown in specific display example 502b, an example of how lotteries are recommended on the lottery home screen 400 may be shown.

[0084] Furthermore, the explanation on the explanation screen 500 may be displayed before the user performs the first draw in the electronic game information processing system 100. In this case, the explanation screen 500 may not be closed until all explanations have been reviewed, including the explanation of the general functions of object recommendation, the explanation of the functions for which objects and draws are recommended based on piece-based recommendation processing, and the explanation of the functions for which draws are recommended based on community-based recommendation processing. For example, on the screen explaining the general functions of object recommendation, the back button 504a and the OK button 504c may be disabled before the explanation of the functions for which objects and draws are recommended based on piece-based recommendation processing is displayed, and on the screen explaining the functions for which objects and draws are recommended based on piece-based recommendation processing, the OK button 504c may be disabled before the explanation of the functions for which draws are recommended based on community-based recommendation processing is displayed.

[0085] Returning to the explanation of the lottery home screen 400 in Figure 16, the coin purchase button 410 is a button to select (click or tap) when purchasing coins. Selecting the coin purchase button 410 will take you to the coin purchase process. This process can be performed in the same way as the conventional coin purchase process. The piece box expansion button 412 is a button to select (click or tap) when expanding the piece box. Selecting the piece box expansion button 412 will take you to the process of expanding the capacity of the piece box that can hold pieces. This process can be performed in the same way as the conventional piece box expansion process.

[0086] The lottery image display area 414 is an area for displaying images that show the contents of various lotteries (for example, Gacha (registered trademark)). The images to be displayed in the lottery image display area 414 are preferably images that express the contents and characteristics of the lottery. For example, it is preferable to use images that express lotteries related to special events, lotteries related to special commemorations, etc. These images can be prepared in advance for each type of lottery and stored in the storage unit 12 of the server 102.

[0087] The single draw button 416 is a button to select (click or tap) when you want to perform a draw of the displayed type only once. When the single draw button 416 is selected, a draw to acquire an object is performed only once. It is preferable to display the amount of coins required for one draw along with the single draw button 416. The multiple draw button 418 is a button to select (click or tap) when you want to perform a draw of the displayed type multiple times. When the multiple draw button 418 is selected, a draw to acquire an object is performed multiple times. It is preferable to display the amount of coins required for multiple draws along with the multiple draw button 418. In this case, it is preferable to set it so that the amount of coins consumed per draw is less when performing a draw with the multiple draw button 418 than when performing a draw with the single draw button 416.

[0088] The featured piece display area 420 is an area that displays several objects that deserve attention from among the objects that can be obtained in the displayed type of lottery. For example, it is preferable to display rare objects that can only be obtained in special event lotteries, or objects that can be obtained with a higher probability than in other types of lotteries, in the featured piece display area 420.

[0089] The piece box selection button 422a is a button that the user selects (clicks or taps) to display the contents of the piece box they are using. The shop selection button 422b is a button that the user selects (clicks or taps) to purchase items in the electronic game. The match selection button 422c is a button that the user selects (clicks or taps) to start a match in the electronic game. The lottery selection button 422d is a button that the user selects (clicks or taps) to start a lottery. That is, by selecting the lottery selection button 422d, the lottery home screen 400 is displayed. The menu selection button 422e is a button that the user selects (clicks or taps) to display the menu screen in the electronic game. These processes are not directly related to the present invention, so a detailed explanation is omitted. The piece box selection button 422a, shop selection button 422b, match selection button 422c, lottery selection button 422d, and menu selection button 422e are preferably displayed on the output unit 26 of the user's client 104 as needed.

[0090] Figure 20 shows an example of the display of the lottery home screen 400 when there are objects and lotteries recommended based on piece-based recommendation processing, and when there are lotteries recommended based on community-based recommendation processing.

[0091] In this case, the lottery home screen 400, which shows the type of lottery being recommended, displays a piece-based recommendation display area 430 and a community-based recommendation display area 432. The piece-based recommendation display area 430 displays information indicating the recommended piece (object) determined in the piece-based recommendation process and the deck to which it was recommended. For example, information such as "Piece X is recommended!" or "Recommended to strengthen your current deck A!" is displayed. The community-based recommendation display area 432 displays information indicating that it is a recommended lottery determined in the community-based recommendation process. For example, information such as "This lottery is popular with 50% of the top 1000 players from last month" is displayed. The top 1000 players are calculated based on the results of events held in the previous month. Additionally, the gacha usage status of users of a specific rank may be displayed.

[0092] Furthermore, it is preferable to display the piece base recommended display area 430 and the piece details button 430a and the deck details button 430b.

[0093] The piece details button 430a is a button that is selected (clicked or tapped) to display information about the recommended piece (object) determined in the piece-based recommendation process. When the piece details button 430a is selected, the piece details screen 600 is displayed as shown in Figure 21.

[0094] The piece details screen 600 includes a piece name (object name) display area 602, a piece image display area 604, a piece information display area 606, a skill display area 608, and a combo skill display area 610. The piece name display area 602 displays the name of the recommended piece (object). The piece image display area 604 displays an image of the recommended piece (object). The piece information display area 606 displays information about the recommended piece (object), such as level, HP, and cost. The skill display area 608 displays information explaining the skills performed by the recommended piece (object). The combo skill display area 610 displays information explaining the combo skills performed by the recommended piece (object).

[0095] Furthermore, if a piece becomes a recommended piece through evolution, a display indicating that the piece can evolve and becomes a recommended piece through evolution may be shown in at least one of the piece base recommendation display area 430 and the piece details screen 600.

[0096] The deck details button 430b is a button that is selected (clicked or tapped) to display information about the deck that was selected in the piece-based recommendation process. When the deck details button 430b is selected, the deck details screen 700 is displayed as shown in Figure 22.

[0097] The deck details screen 700 includes a deck name display area 702, a description area 704, a deck contents display area 706, and a close button 708. The deck name display area 702 displays the name of the deck that was targeted in the piece-based recommendation process. The description area 704 displays a description of the deck that was targeted in the piece-based recommendation process. For example, a description such as "This displays the deck targeted for recommended pieces. Since it refers to data from the previous day or earlier, it may differ from the current deck information" may be displayed. The deck contents display area 706 displays information about the deck that was targeted in the piece-based recommendation process. The information about the deck preferably includes the user name, images showing the pieces that make up the deck, and information such as the hit points (HP), attack power (ATK), and cost of the pieces that make up the deck. The close button 708 is a button to select (click or tap) when returning from the deck details screen 700 to the previous screen.

[0098] Furthermore, as shown in Figure 23, an AI mark 430c may be displayed on the lottery home screen 400. By operating the AI ​​mark 430c, the user scrolls the image to the lottery home screen 400 that shows the lottery recommended based on piece-based recommendation processing or the lottery recommended based on community-based recommendation processing. The AI ​​mark 430c displays information indicating the direction in which the lottery home screen 400 showing the lottery recommended based on piece-based recommendation processing or the lottery recommended based on community-based recommendation processing will be displayed. For example, if the lottery home screen 400 showing the recommended lottery is displayed by scrolling the image upwards, a symbol (arrow, etc.) indicating upwards will be displayed on the AI ​​mark 430c, as shown in Figure 23. Conversely, if the lottery home screen 400 showing the recommended lottery is displayed by scrolling the image downwards, a symbol (arrow, etc.) indicating downwards will be displayed on the AI ​​mark 430c.

[0099] When a user selects (clicks or taps) the AI ​​mark 430c, the lottery home screen 400 is scrolled in the direction indicated on the AI ​​mark 430c. Then, as shown in Figure 20, the image is scrolled and displayed up to the lottery home screen 400 showing the lottery recommended based on piece-based recommendation processing or the lottery recommended based on community-based recommendation processing.

[0100] Thus, even when a different lottery home screen 400 is displayed than the lottery home screen 400 that shows the lottery recommended based on piece-based recommendation processing or the lottery recommended based on community-based recommendation processing, selecting the AI ​​mark 430c allows easy access to the lottery home screen 400 that shows the lottery recommended based on piece-based recommendation processing or the lottery recommended based on community-based recommendation processing.

[0101] Furthermore, if only draws recommended based on piece-based recommendation processing exist and no draws recommended based on community-based recommendation processing exist, the draw home screen 400 may display only the piece-based recommendation display area 430. Also, if only draws recommended based on community-based recommendation processing exist and no draws recommended based on piece-based recommendation processing exist, the draw home screen 400 may display only the community-based recommendation display area 432. In addition, if the draws recommended based on piece-based recommendation processing and the draws recommended based on community-based recommendation processing are different, the draw home screen 400 showing the respective draws may display the piece-based recommendation display area 430 and the community-based recommendation display area 432, respectively.

[0102] Although embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, and various modifications are possible without departing from the spirit of the invention.

[0103] [Structure of the invention] [Configuration 1] An object recommendation system characterized by identifying and proposing to the user objects that the user does not own and that are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns. [Configuration 2] The object recommendation system described in Configuration 1, An object recommendation system characterized by presenting the user with information indicating that the recommended object is available if the recommended object is available. [Configuration 3] An object recommendation system as described in Configuration 1 or 2, An object recommendation system characterized by identifying and proposing the recommended objects to the user for each of the decks the user is using. [Structure 4] An object recommendation system described in any one of the configurations 1 to 3, An object recommendation system characterized in that the display of suggested objects to the user can be switched on or off. [Composition 5] Computers, An object recommendation program characterized by functioning to identify and propose to the user objects that the user does not own and that are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns. [Composition 6] On the computer, An object recommendation method characterized by performing a process to identify objects that the user does not own and that are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns, and to propose them to the user as recommended objects. [Explanation of symbols]

[0104] 10 Processing Unit, 12 Memory Unit, 14 Input Unit, 16 Output Unit, 18 Communication Unit, 20 Processing Unit, 22 Memory Unit, 24 Input Unit, 26 Output Unit, 28 Communication Unit, 100 Electronic Game Information Processing System, 102 Server, 104 Client, 106 Information Communication Network, 200 Deck Screen, 202 Player Name Display Area, 204 Cost Display Area, 206 Hit Point Display Area, 208 Attack Power Display Area, 210 Object Display Area, 300 Battle Screen, 302 Player Name Display Area, 304 Opponent Player Hit Point Display Area, 306 Opponent Player Name Display Area, 308 Board Display Area, 310 Hit Point Display Area, 312 Piece Display Area, 400 Lottery Home Screen, 402 User Name Display Area, 404 User Information Display Area, 406 Coin Display Area, 408 Lottery information setting area, 408a Object recommended setting switch, 408b Help button, 410 Coin purchase button, 412 Piece box expansion button, 414 Lottery image display area, 416 Single draw button, 418 Multiple draw button, 420 Featured piece display area, 422a Piece box selection button, 422b Shop selection button, 422c Opponent selection button, 422d Lottery selection button, 422e Menu selection button, 430 Piece base recommended display area, 430a Piece details button, 430b Deck details button, 430c AI mark, 432 Community base recommended display area, 500 Explanation screen, 502 Explanation display area, 502a Specific display example, 502b Specific display example, 504a Back button, 504b Forward button, 504c OK button, 600 Piece details screen, 602 Piece name (object name) display area, 602 Piece name display area, 604 Piece image display area, 606 Piece information display area, 608 Skill display area, 610 Combo skill display area, 700 Deck details screen, 702 Deck name display area, 704 Description area, 706 Deck contents display area, 708 Close button.

Claims

1. An object recommendation system characterized by identifying and proposing to the user objects that the user does not own and that are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns.

2. An object recommendation system according to claim 1, An object recommendation system characterized by presenting the user with information indicating that the recommended object is available if the recommended object is available.

3. An object recommendation system according to claim 1 or 2, An object recommendation system characterized by identifying and proposing the recommended objects to the user for each of the decks the user is using.

4. An object recommendation system according to claim 1, An object recommendation system characterized in that the display of suggested objects to the user can be switched on or off.

5. Computers, An object recommendation program characterized by functioning to identify and propose to the user objects that the user does not own and that are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns.

6. On the computer, An object recommendation method characterized by performing a process to identify objects that the user does not own and that are recommended for use in the deck, based on the objects included in the deck the user is using and the objects the user owns, and to propose them to the user as recommended objects.

Images