Abstract: Using user-specific prediction models, it is possible to present an individualized view of messages generated by users playing a shared instance of a video game. Further, users with different subjective views of what is offensive may be presented with different forms or annotations of a message. By personalizing the views of messages generated by users, it is possible to reduce or eliminate the toxic environment that sometimes forms when players, who may be strangers to each other and may be located in disparate locations play a shared instance of a video game. Further, the user-specific prediction models may be adapted to filter or otherwise annotate other undesirable messages that may not be offensive, such as a message generated by one user in a video game that includes a solution to an in-game puzzle that another user may not desire to read as it may spoil the challenge for the user.

Abstract: Using user-specific prediction models, it is possible to present an individualized view of messages generated by users playing a shared instance of a video game. Further, users with different subjective views of what is offensive may be presented with different forms or annotations of a message. By personalizing the views of messages generated by users, it is possible to reduce or eliminate the toxic environment that sometimes forms when players, who may be strangers to each other and may be located in disparate locations play a shared instance of a video game. Further, the user-specific prediction models may be adapted to filter or otherwise annotate other undesirable messages that may not be offensive, such as a message generated by one user in a video game that includes a solution to an in-game puzzle that another user may not desire to read as it may spoil the challenge for the user.

Abstract: A method and system are presented that can model a video game in a state graph. The nodes can be configured to represent actions are performable in the video game. Using the state graph and test logs that journal actions performed by testers that played the video game, a plurality of scripts can be generated representing actions different users may perform when playing the video game. Further, by applying a probabilistic analysis to the test logs, weights can be applied to the state graph that reflect the likelihood that a user performs a particular action subsequent to a previously performed action. By generating a random walk of the state diagram, a script to simulate a player may be generated. By generating many scripts to simulate many players, it is possible to perform full scale realistic testing of the video game that matches the way human users play the video game.

Abstract: Systems and methods are disclosed to receive an indication that a buyer has placed an item in a virtual shopping cart. One or more conversion shipping options associated with shipping options used to ship one or more previously purchased items purchased by the buyer may be determined. One or more non-conversion shipping options associated with shipping options presented to the buyer with one or more unpurchased items previously placed in a virtual shopping cart by the buyer but not purchased by the buyer may be determined. A plurality of conversion probabilities may be determined for a plurality of different shipping options for the item in the virtual shopping cart based at least in part on the conversion shipping options and the non-conversion shipping options. In some embodiments, a shipping option may be selected based on the plurality of different shipping options and the plurality of conversion probabilities.

Abstract: Methods, systems, and apparatus for controlling an inventory of an item for sale are described. A demand for the item and an inventory of the item are projected. A recommended future time period for listing the item for sale is determined based on the projected demand and the projected inventory and is provided to a user listing the item on an online marketplace. A user-selected listing time period is obtained and an item record generated comprising an item description, the item record being associated with the user-selected listing time period.