Systems, devices, and methods for improved affix-based domain name suggestion
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.
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, wherein the list of affixes comprises words from a training set of textual data;
determining a conditional probability for affixes in the list of affixes using a language model, wherein the language model is trained using the training set of textual data, wherein the conditional probability indicates a desirability rating for a combination of a respective affix in the list of affixes with the textual data;
ranking the 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 , wherein the language model comprises a feed-forward neural network with one or more non-linear hidden layers.
5. The system of claim 1 , wherein the language model comprises a log-linear language model.
6. The system of claim 1 , wherein the training set of textual data is a domain name system zone file.
7. The system of claim 1 , wherein the conditional probabilities for the affixes are position dependent.
8. The system of claim 1 , wherein the conditional probabilities for the affixes are position independent.
9. 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.
10. 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.
11. The system of claim 1 , the operations further comprising displaying the domain name suggestions in a browser.
12. 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, wherein the list of affixes comprises words from a training set of textual data;
determining a conditional probability for affixes in the list of affixes using a language model, wherein the language model is trained using the training set of textual data, wherein the conditional probability indicates a desirability rating for a combination of a respective affix in the list with the textual data;
ranking the 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.
13. The method of claim 12 , wherein at least one token of the one or more tokens comprises a plurality of words.
14. The method of claim 12 , wherein the list of affixes comprises generic top level domains.
15. The method of claim 12 , wherein the language model comprises a feed-forward neural network with one or more non-linear hidden layers.
16. The method of claim 12 , wherein the language model comprises a log-linear language model.
17. The method of claim 12 , wherein the training set of textual data is a domain name system zone file.