PATENT CLAIM ANALYSIS

Application Number: 15971901
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-09
Patent Classification: ["463", "031000"]

Abstract:
Targeted recommendations may be provided to specific user segments. The users may be segmented on or more user parameters that facilitate targeted provision of recommendations to the individual segments of users. A recommendation may prompt a user to take a recommended action in the game.

Claim (Index 13):
A computer-implemented method of providing different recommendations to users of a virtual space and assess relative effectiveness of the provided recommendations, wherein effectiveness is a function of retention of the users that perform actions in accordance with the provided recommendations, the method being implemented in a computer system comprising one or more physical processors, the method comprising:\n executing an instance of a virtual space; implementing the instance of the virtual space to facilitate participation by the one or more users in a game within the space by:\n (i) determining view information from the instance and transmitting the view information to one or more client computing platforms associated with the one or more users that facilitate presentation of views of the virtual space to the one or more users by the one or more client computing platforms, and \n (ii) receiving control inputs entered by the one or more users through the one or more client computing platforms, wherein the control inputs facilitate interaction between the one or more users and the virtual space; \n obtaining values of respective user parameters for the one or more users, the respective user parameters comprising a first parameter;\n obtain a first segment of users from the one or more users; \n generating automatically, by the one or more physical processors, a first set of recommendations for the first segment of users, wherein a recommendation prompts a user to take a recommended action in the game, the first set of recommendations including at least a first recommendation and a second recommendation, and wherein the first recommendation recommends a first recommended action and the second recommendation recommends a second recommended action that is different from the first recommended action; \n effectuating delivery of the first and second recommendations to different users in the first segment of users; \n tracking responses of the users of the first segment to the first and second recommendations by:\n (i) determining whether individual users in the first subset of users have effectuated performance of the first recommended action, \n (ii) determining whether individual users in the second subset of users have effectuated performance of the second recommended action, \n (iii) determining a first metric of effectiveness for the first recommendation based on retention of those users in the first subset of users who effectuated performance of the first recommended action, and \n (iv) determining a second metric of effectiveness for the second recommendation based on retention of those users in the second subset of users who effectuated performance of the second recommended action; \n \n generating a new recommendation for one or more subsets of an individual segment of the one or more users based on one or more of the first recommendation, the second recommendation, the first metric of effectiveness, and/or the second metric of effectiveness; and \n effectuating delivery of the new recommendation to one or more appropriate users.

Metadata:
- Claim Count in Document: 50.0
- Percentile: 93.0
- Lexical Diversity: 1.45455
- Patent Class: 463.0
- Transitional Phrase Type: open
- Component Type: 1
- Foreign Priority: False
- Related Applications: ['15345756', '14658111', '13633782', '14320550', '14107914']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.3666969195175648
- 35 USC 102 Novelty (BERT): 0.5030098776636746
- Combined Prediction Score: 0.3803282153321757
- Mean Citation Score: 291.30187400000005
- Max Citation Score: 344.66776
- Similarity Product: 314.28019367900845

Labels:
- Claim Label 101: 0
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 1
- Combined Label: 0
- Label 101 Adjusted: 0

Dataset: test