Automated discovery of gaming preferences

• US 9,084,932 B2
• Filed: 01/10/2013
• Issued: 07/21/2015
• Est. Priority Date: 01/13/2012
• Status: Active Grant

• Current Assignee: GTECH Canada ULC
• Original Assignee: GTECH Canada ULC
• Inventors: Gadher, Bharat Kumar, McIntyre, Andrew R., Idris, Fayez
• Primary Examiner(s): PIERCE, DAMON JOSEPH
• Application Number:
  US13/738,790
• Publication Number:
  US 20130184071A1
• Time in Patent Office: 922 Days
• Field of Search: 463/16, 463/25, 463/29, 463/42
• US Class Current: 1/1
• CPC Class Codes: G06F 12/00 Accessing, addressing or allocating within memory systems or architectures digital input from, or digital output to record carriers, e.g. to disk storage units, G06F3/06
• CPC Class Codes: G07F 17/3225 Data transfer within a gaming system, e.g. data sent between gaming machines and users
• CPC Class Codes: G07F 17/3227 Configuring a gaming machine, e.g. downloading personal settings, selecting working parameters
• CPC Class Codes: G07F 17/3237 about the players, e.g. profiling, responsible gaming, strategy/behavior of players, location of players
• CPC Class Codes: G07F 17/3239 Tracking of individual players

Abstract

Systems and methods for automated discovery of gaming preferences and delivery of gaming choices based gaming preferences are disclosed. The systems and methods may operate in real time and may detect and analyze data representing various game features and/or game player behavior and match the data with predetermined models, profiles or game player types. Game choices may then be presented to the game player based on the analysis of the data. Systems and methods to analyze and categorize the game player behavior are also disclosed, including mining data in a cluster model based analysis to identify and develop the models, profiles or game player types and to select the games to be provided for each of the identified models, profiles or game player types. A different collection of games may be provided for each of the identified models, profiles or game player types.

Claims

1. A computer implemented method of operating a wagering game system in real time, comprising the steps of:

establishing a communication link using network infrastructure between a plurality of gaming devices and a central recommender processor, wherein each gaming device is operated by an anonymous player that is not registered with the wagering game system, wherein each gaming device is programmed to carry out game functions of receiving wagering and game instructions, determining a game outcome, and determining an award;

generating a gaming and play behavior model by partitioning stored play data into a plurality of game session patterns, wherein each game session pattern corresponds to a time period and indicates occurrence of game factors over the time period;

detecting, at the recommender processor, that a current anonymous player begins to play a game or indicates a desire to play the game using a first gaming device of the plurality of gaming devices;

collecting, by the recommender processor from the first gaming device using the communication link, a first set of real time game data related to game factors for game play in an ongoing game by the anonymous player;

determining, by the recommender processor, that the first set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour for the current anonymous player using the plurality of game session patterns;

determining, by the recommender processor, at least one game player type from among a set of predefined game player types for the current anonymous game player based on the first set of real time game data and the plurality of game session patterns; and

transmitting from the recommender processor to the first gaming device using the communication link, a selection of games identified for the current anonymous player using the determined at least one game player type.

2. The method of claim 1, wherein the step of generating a gaming and play behavior model comprises:

performing a cluster analysis of the plurality of game sessions to group game sessions into different clusters, wherein each game cluster is linked to one or more game player types, and wherein the method further comprises identifying a cluster of game session patterns.

3. The method of claim 1, wherein the step of generating a gaming and play behavior model comprises:

detecting indicators from within the first set of real time game data.

4. The method of claim 1, wherein the step of generating a gaming and play behavior model comprises:

detecting trends within the first set of real time game data.

5. The method of claim 1, wherein the step of determining comprises:

matching, by the recommender processor, the first set of real time game data to a first set of game session patterns of the plurality of game session patterns, wherein the first set of game session patterns are associated with at least one game player type.

6. The method of claim 1, wherein the first set of real time game data represents at least one game factor selected from the group consisting of:

game session length, play behavior, game behavior, game language, game location, game selection, elapsed time with one game, wagering behavior, game type, game theme, wager amounts, wager denominations, play rates, typical bonus values, game brand, prize distributions, amounts of incremental wagers, frequency of wagering, for instance the presence or absence of multiple rounds of wagering in a game, the number of rounds of wagers permitted in a game, maximum wager amounts permitted, minimum wager amounts permitted, amount of wagering, elapsed time between selected events for instance starting a new game, reaction to bonus rounds, reaction to progressive outputs, pay table features, amount of incremental wagers, frequency of wagering, elapsed time for player reaction, amount of wagering, elapsed time between wagers, frequency of player action, game rules, game complexity, ability for a player to control or have an effect on a game outcome, whether an outcome is predetermined, whether parallel wagering is provided, average game speed, average wager amounts, average wager rate, presence or frequency of bonus rounds, presence and frequency of progressive outputs, payout percentages, win rates, win percentages, loss rates, loss percentages, use of special features, frequency of use of special features, number of lines played, total amount wagered, and type of payment received.

7. The method of claim 1, wherein the step of collecting a first set of real time game data involves collecting data from the moment that the player begins to play the game or indicates a desire to play the game.

8. The method of claim 1, wherein the step of collecting a first set of real time game data involves collecting data for a predetermined length of time.

9. The method of claim 1 further comprising the step of:

receiving a selection of another game from the selection of games to play from the current anonymous player using the first gaming device, and collecting, by the recommender processor from the first gaming device using the communication link, at the moment of the detection that the current anonymous player begins to play the other game or indicates a desire to play the other game, a second set of real-time game data related to game factors for game play in an ongoing live game of the other game.

10. The method of claim 1, wherein the wagering game system holds no player account identifying the current anonymous player to the wagering game system.

11. The method of claim 1, wherein the wagering game system holds no information identifying the current anonymous player to the wagering game system.

12. The method of claim 1, further comprising the step of:

updating a previously-determined at least one game player type based on an additional set of real time game data, the additional set of real time game data related to game factors for an additional time period of game play in an ongoing game by the current anonymous player.

13. The method of claim 12, wherein the first set of real time game data and the additional set of real time game data are related to distinct time periods.

14. The method of claim 12, wherein the first set of real time game data and the additional set of real time game data are related to overlapping time periods.

15. The method of claim 14, wherein the additional set of real time game data is larger than the first set of real time game data.

16. The method of claim 14, wherein the additional set of real time game data relates to a longer time period of game play than the first set of real time game data.

17. The method of claim 1, wherein the step of determining at least one game player type further involves factoring in geographical data related to a location of the ongoing game.

18. The method of claim 1, wherein the step of determining at least one game player type further involves factoring in language data related to a language of the ongoing game.

19. The method of claim 1, further comprising the step of receiving an indication of agreement to monitoring of game play from the current anonymous player.

20. The method of claim 1, further comprising the step of receiving an indication of agreement to collection of game play data from the current anonymous player.

21. The method of claim 1 wherein a first game session pattern of the plurality of game session patterns corresponds to a first time period and a second game session pattern of the plurality of game session patterns corresponds to a second time period, wherein the first time period is longer than the second time period.

22. The method of claim 1, further comprising:

detecting, at the recommender processor, in real time or near real time that another current anonymous player begins to play a game or indicates a desire to play the game using a second gaming device of the plurality of gaming devices;

collecting, by the recommender processor from the second gaming device using the communication link, at the moment of the detection that the other current anonymous player begins to play the game or indicates the desire to play the game, a second set of real time game data defining occurrence of game factors for game play in another ongoing live game;

determining, by the recommender processor, that the second set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour using the plurality of game session patterns;

matching, by the recommender processor, the second set of real time game data to a first set of game session patterns of the plurality of game session patterns;

determining, by the recommender processor, another at least one game player type from among the set of predefined game player types for the game player based on the second set of game session patterns; and

transmitting from the recommender processor to the second gaming device using the communication link, a selection of games identified for the determined other at least one game player type.

23. A wagering game system comprising:

a plurality of electronic gaming machines, wherein each electronic gaming machine is configured to provide a selection of wagering games to an anonymous player that is not registered with the wagering game system;

a recommender processor configured to;

generate a gaming and play behavior model by partitioning stored play data into a plurality of game session patterns, wherein each game session pattern corresponds to a time period and indicates occurrence of game factors over the time period;

detect that a current anonymous player begins to play a game or indicates a desire to play the game at a first electronic gaming machine using a communication link;

collect from the first electronic gaming machine using the communication link, a first set of real time game data related to game factors for game play in an ongoing game by the anonymous player;

determine that the first set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour for the current anonymous player using the plurality of game session patterns;

determine at least one game player type from among a set of predefined game player types for the anonymous player based on the first set of real time game data related to game play by the current anonymous player and the plurality of game session patterns; and

transmit to the electronic gaming machine using the communication link, a selection of games identified for the current anonymous player using the determined at least one game player type; and

the communication link of network infrastructure connecting the electronic gaming machine to the recommender processor.

24. The system of claim 23, wherein the recommender processor is configured to generate a gaming and play behavior model by performing a cluster analysis of the plurality of game sessions to group game sessions into different clusters, wherein each game cluster is linked to one or more game player types, and wherein the method further comprises identifying a cluster of game session patterns.

25. The system of claim 23, wherein the recommender processor is configured to match the first set of real time game data to a first set of game session patterns of the plurality of game session patterns, wherein the first set of game session patterns are associated with at least one game player type.

26. The system of claim 23, wherein the first set of real time game data represents at least one game factor selected from the group consisting of:

game session length, play behavior, game behavior, game language, game location, game selection, elapsed time with one game, wagering behavior, game type, game theme, wager amounts, wager denominations, play rates, typical bonus values, game brand, prize distributions, amounts of incremental wagers, frequency of wagering, for instance the presence or absence of multiple rounds of wagering in a game, the number of rounds of wagers permitted in a game, maximum wager amounts permitted, minimum wager amounts permitted, amount of wagering, elapsed time between selected events for instance starting a new game, reaction to bonus rounds, reaction to progressive outputs, pay table features, amount of incremental wagers, frequency of wagering, elapsed time for player reaction, amount of wagering, elapsed time between wagers, frequency of player action, game rules, game complexity, ability for a player to control or have an effect on a game outcome, whether an outcome is predetermined, whether parallel wagering is provided, average game speed, average wager amounts, average wager rate, presence or frequency of bonus rounds, presence and frequency of progressive outputs, payout percentages, win rates, win percentages, loss rates, loss percentages, use of special features, frequency of use of special features, number of lines played, total amount wagered, and type of payment received.

27. The system of claim 23, wherein the recommender processor is configured to collect the first set of real time game data by collecting data from the moment that the player begins to play the game or indicates a desire to play the game.

28. The system of claim 23, wherein the recommender processor is configured to receive a selection of another game from the selection of games to play from the current anonymous player using the first gaming device, and collect from the first gaming device using the communication link, at the moment of the detection that the current anonymous player begins to play the other game or indicates a desire to play the other game, a second set of real-time game data related to game factors for game play in an ongoing live game of the other game.

29. The system of claim 23, wherein the wagering game system holds no player account identifying the current anonymous player to the wagering game system.

30. The system of claim 23, wherein the wagering game system holds no information identifying the current anonymous player to the wagering game system.

31. The system of claim 23, wherein the recommender processor is configured to update a previously-determined at least one game player type based on an additional set of real time game data, the additional set of real time game data related to game factors for an additional time period of game play n an ongoing game by the current anonymous player.

32. The system of claim 23, wherein the first set of real time game data and the additional set o* real time game data are related to distinct time periods.

33. The system of claim 23, wherein the first set of real time game data and the additional set of real time game data are related to overlapping time periods.

34. The system of claim 23, wherein the additional set of real time game data is larger than the first set of real time game data.

35. The system of claim 23, wherein the additional set of real time game data relates to a longer time period of game play than the first set of real time game data.

36. The system of claim 23, wherein the recommender processor is configured to determine the at least one game player type by factoring in geographical data related to a location of the ongoing game.

37. The system of claim 23, wherein a first game session pattern of the plurality of game session patterns corresponds to a first time period and a second game session pattern of the plurality of game session patterns corresponds to a second time period, wherein the first time period is longer than the second time period.

38. The system of claim 23, wherein the recommender processor is configured to:

detect in real time or near real time that another current anonymous player begins to play a game or indicates a desire to play the game using a second gaming device of the plurality of gaming devices;

collect, from the second gaming device using the communication link, at the moment of the detection that the other current anonymous player begins to play the game or indicates the desire to play the game, a second set of real time game data defining occurrence of game factors for game play in another ongoing live game;

determine that the second set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour using the plurality of game session patterns;

match the second set of real time game data to a first set of game session patterns of the plurality of game session patterns;

determine another at least one game player type from among the set of predefined game player types for the game player based on the second set of game session patterns; and

transmit to the second gaming device using the communication link, a selection of games identified for the determined other at least one game player type.

39. A non-transitory computer readable storage medium having instructions stored therein thereon, the instructions, when executed, being operable to cause a computerized wagering game system to:

generate a gaming and play behavior model by partitioning play data into a plurality of game session patterns, each game session pattern corresponds to a time period and indicates occurrence of game factors over the time period;

detect that an anonymous player begins to play a game or indicates a desire to play the game using an electronic gaming machine, wherein the anonymous player is not registered with the wagering game system;

collect from the electronic gaming machine using a communication link, a first set of real time game data related to game factors for game play in an ongoing game by the anonymous player;

determine that the first set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour for the anonymous player using the plurality of game session patterns;

determine at least one game player type from among a set of predefined game player types for the anonymous player based on the first set of real time game data related to game play by the anonymous player and the plurality of game session patterns; and

transmit to the electronic gaming machine using the communication link, a selection of games identified for the anonymous player using the determined at least one game player type.

40. The computer readable storage medium of claim 39, wherein a first game session pattern of the plurality of game session patterns corresponds to a first time period and a second game session pattern of the plurality of game session patterns corresponds to a second time period, wherein the first time period is longer than the second time period.

41. The computer readable storage medium of claim 39, the instructions, when executed, being operable to cause the computerized wagering game system to:

detect in real time or near real time that another current anonymous player begins to play a game or indicates a desire to play the game using a second gaming device of the plurality of gaming devices;

collect, at the moment of the detection that the other current anonymous player begins to play the game or indicates the desire to play the game, a second set of real time game data defining occurrence of game factors for game play in another ongoing live game;

determine that the second set of real time game data has been collected for a minimum length of time of game play required to categorize game behaviour using the plurality of game session patterns;

match the second set of real time game data to a first set of game session patterns of the plurality of game session patterns;

determine another at least one game player type from among the set of predefined game player types for the game player based on the second set of game session patterns; and

transmit a selection of games identified for the determined other at least one game player type.