As provided herein, a webpage navigation of a user over a timeframe and a second webpage navigation of a second user over a second timeframe may be received. A time-variant variable-order Markov model, comprising a context tree, may be generated utilizing the webpage navigation and the second webpage navigation. A third webpage navigation of a third user may be received. A probability that the third user may interact with content, that the third user is a non-human entity, and/or that the third user will access a website may be determined based upon an evaluation of the third webpage navigation using the time-variant variable-order Markov model. A second client device is instructed to present the content to the third user, to present a human verification mechanism to the third user, and/or to instruct a server, providing the website, to alter a server capacity for the website.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A client device for user action prediction, the client device comprising: a processor; a display; and a memory storing instructions that, when executed on the processor, provide a prediction component configured to: receive a webpage navigation of a user over a timeframe; receive a second webpage navigation of a second user over a second timeframe, the second timeframe overlapping the timeframe; generate a time-variant variable-order model, comprising a context tree, utilizing the webpage navigation and the second webpage navigation; receive a third webpage navigation of a third user; determine a probability that the third user will interact with content based upon an evaluation of the third webpage navigation using the time-variant variable-order model; and responsive to the probability exceeding a threshold, instruct a second client device to present the content to the third user. 2. The client device of claim 1, the time-variant variable-order model comprising a Markov model. 3. The client device of claim 1, the prediction component configured to: receive an extraction of the webpage navigation of the user; transform the webpage navigation into a format; and load the webpage navigation, according to the format, into the time-variant variable-order model. 4. The client device of claim 1, the prediction component configured to: receive an extraction of the second webpage navigation of the second user; transform the second webpage navigation into a format; and load the second webpage navigation into the time-variant variable-order model. 5. The client device of claim 1, the prediction component configured to generate the time-variant variable-order model utilizing: in window aggregation, the in window aggregation outputting: a webpage location of the user, based upon the webpage navigation, for one or more time points; and a second webpage location of the second user, based upon the second webpage navigation, for one or more second time points. 6. The client device of claim 1, the time-variant variable-order model configured to at least one of: identify a first trend indicating the third user has a decreased probability of interacting with the content; or identify a second trend indicating the third user has an increased probability of interacting with the content. 7. The client device of claim 1, the prediction component configured to: prune a branch of the context tree based upon the branch corresponding to an irrelevant node. 8. A method for user action prediction, comprising: receiving a webpage navigation of a user over a timeframe; receiving a second webpage navigation of a second user over a second timeframe, the second timeframe overlapping the timeframe; generating a time-variant variable-order model, comprising a context tree, utilizing the webpage navigation and the second webpage navigation; receiving a third webpage navigation of a third user; determining a probability that the third user is a non-human entity based upon an evaluation the third webpage navigation using the time-variant variable-order model; and responsive to the probability exceeding a threshold, identifying the third user as the non-human entity. 9. The model of claim 8, the time-variant variable-order model comprising a Markov model. 10. The method of claim 8, comprising: receiving an extraction of the webpage navigation of the user; transforming the webpage navigation into a format; and loading the webpage navigation, according to the format, into the time-variant variable-order model. 11. The method of claim 8, comprising: receiving an extraction of the second webpage navigation of the second user; transforming the second webpage navigation into a format; and loading the second webpage navigation, according to the format, into the time-variant variable-order model. 12. The method of claim 8, comprising: utilizing in window aggregation to output: a webpage location of the user, based upon the webpage navigation, for one or more time points; and a second webpage location of the user, based upon the second webpage navigation, for one or more second time points. 13. The method of claim 8, comprising: pruning a branch of the context tree based upon the branch corresponding to an irrelevant node. 14. The method of claim 8, comprising: responsive to identifying the third user as the non-human entity, presenting the third user with a human verification mechanism. 15. A client device for user action prediction, the client device comprising: a processor; a display; and a memory storing instructions that, when executed on the processor, provide a prediction component configured to: receive a webpage navigation of a user over a timeframe; receive a second webpage navigation of a second user over a second timeframe, the second timeframe overlapping the timeframe; generate a time-variant variable-order model, comprising a context tree, utilizing the webpage navigation and the second webpage navigation; receive a third webpage navigation of a third user; determine a probability that the third user will interact with a website based upon an evaluation of the third webpage navigation using the time-variant variable-order model; and responsive to the probability exceeding a threshold, instruct a server, providing the website, to alter a server capacity for the website. 16. The client device of claim 15, the time-variant variable-order model comprising a Markov model. 17. The client device of claim 15, the prediction component configured to: prune a branch of the context tree based upon the branch corresponding to an irrelevant node. 18. The client device of claim 15, the prediction component configured to: receive an extraction of the webpage navigation of the user; transform the webpage navigation into a format; load the webpage navigation, according to the format, into the time-variant variable-order model; receive an extraction of the second webpage navigation of the second user; transform the second webpage navigation into the format; and load the second webpage navigation, according to the format, into the time-variant variable-order model. 19. The client device of claim 15, the prediction component configured to generate the time-variant variable-order model utilizing: in window aggregation, the in window aggregation outputting: a webpage location of the user, based upon the webpage navigation, for one or more time points; and a second webpage location of the user, based upon the second webpage navigation, for one or more second time points. 20. The client device of claim 15, the time-variant variable-order model configured to at least one of: identify a first trend indicating the third user has a decreased probability of interacting with the website; or identify a second trend indicating the third user has an increased probability of interacting with the website.