Embodiments relate to systems, devices, and computing-implemented methods for generating domain name suggestions by obtaining a domain name suggestion input that includes textual data, segmenting the textual data into tokens, obtaining a list of possible affixes to the textual data, determining conditional probabilities for the possible affixes using a language model, ranking the list of possible affixes based on the conditional probabilities to generate a ranked list of affixes, and generating domain name suggestions based on the ranked list of affixes.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system comprising: a processing system of a device comprising one or more processors; and a memory system comprising one or more computer-readable media, wherein the one or more computer-readable media contain instructions that, when executed by the processing system, cause the processing system to perform operations comprising: obtaining a domain name suggestion input comprising textual data; segmenting the textual data into one or more tokens; obtaining a list of affixes; determining conditional probabilities for the affixes in the list of affixes using a language model; ranking the list of affixes based on the conditional probabilities to generate a ranked list of affixes; and generating domain name suggestions based on the ranked list of affixes. 2. The system of claim 1, wherein at least one token of the one or more tokens comprises a plurality of words. 3. The system of claim 1, wherein the list of affixes comprises generic top level domains. 4. The system of claim 1, the operations further comprising training the language model using a training set of textual data. 5. The system of claim 4, wherein the list of affixes comprises words from the training set of textual data. 6. The system of claim 4, wherein the language model comprises a feed-forward neural network with one or more non-linear hidden layers. 7. The system of claim 4, wherein the language model comprises a log-linear language model. 8. The system of claim 4, wherein the training set of textual data is a domain name system zone file. 9. The system of claim 1, wherein the conditional probabilities for the list of affixes are position dependent. 10. The system of claim 1, wherein the conditional probabilities for the list of affixes are position independent. 11. The system of claim 1, wherein generating domain name suggestions based on the ranked list of affixes comprises generating domain name suggestions based on top ranked affixes. 12. The system of claim 1, wherein generating domain name suggestions based on the ranked list of affixes comprises generating domain name suggestions based on affixes associated with conditional probabilities that meet or exceed a threshold. 13. The system of claim 1, the operations further comprising displaying the domain name suggestions in a browser. 14. A method comprising: obtaining a domain name suggestion input comprising textual data; segmenting the textual data into one or more tokens; obtaining a list of affixes; determining conditional probabilities for the affixes in the list of affixes using a language model; ranking the list of affixes based on the conditional probabilities to generate a ranked list of affixes; and generating domain name suggestions based on the ranked list of affixes. 15. The method of claim 14, wherein at least one token of the one or more tokens comprises a plurality of words. 16. The method of claim 14, wherein the list of affixes comprises generic top level domains. 17. The method of claim 14, further comprising training the language model using a training set of textual data. 18. The method of claim 17, wherein the language model comprises a feed-forward neural network with one or more non-linear hidden layers. 19. The method of claim 17, wherein the language model comprises a log-linear language model. 20. The method of claim 17, wherein the training set of textual data is a domain name system zone file.