Systems, devices, and methods for improved affix-based domain name suggestion

Abstract

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.

What is claimed is: 
     
         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 an input comprising textual data, wherein the textual data is segmentable into one or more words; 
 obtaining a list of affixes; 
 determining conditional probabilities for affixes in the list of affixes, wherein each conditional probability represents a value assigned to a respective affix, the value indicating a likelihood that adding the affix to the one or more words of the textual data results in a desirable domain name; 
 ranking the affixes based on the conditional probabilities to generate a ranked list of affixes; and 
 providing one or more domain name suggestions based on the ranked list of affixes. 
   
     
     
         2 . The system of  claim 1 , wherein the list of affixes comprises generic top-level domains (gTLDs), wherein the gTLDs are contextually relevant to the textual data. 
     
     
         3 . The system of  claim 2 , wherein the gTLDs in the list of affixes are based on at least one of:
 available gTLDs;   words in a dictionary for a selected language;   words in a dictionary for a determined language of the textual data;   words from a dictionary with a selected syntactical function (e.g., nouns); or   gTLDs from domain names in a zone file.   
     
     
         4 . The system of  claim 2 , wherein determining conditional probabilities for affixes in the list of affixes comprises determining conditional probabilities for the gTLDs in the list of affixes,
 wherein the conditional probability represents a value assigned to the gTLD, and   wherein the value assigned to the gTLD indicates the likelihood that a domain name with the textual data and the gTLD results in a desirable domain name.   
     
     
         5 . The system of  claim 4 , wherein determining conditional probabilities for the gTLDs comprises assigning the conditional probabilities to the gTLDs using a language model. 
     
     
         6 . The system of  claim 1 , wherein determining a conditional probability for an affix in the list of affixes comprises assigning a conditional probability based on a position of the affix positioned in the textual data. 
     
     
         7 . The system of  claim 1 , wherein determining conditional probabilities for affixes in the list of affixes comprises determining a plurality of conditional probabilities for an affix in the list of affixes. 
     
     
         8 . The system of  claim 7 , wherein determining a plurality of conditional probabilities for the affix in the list of affixes comprises two or more of:
 assigning a first conditional probability for adding the affix as a prefix to the one or more words of the textual data;   assigning a second conditional probability for adding the affix between two particular words in the textual data; or   assigning a third conditional probability for adding the affix as a suffix to the one or more words of the textual data.   
     
     
         9 . The system of  claim 1 , wherein determining conditional probabilities for affixes in the list of affixes comprises assigning conditional probabilities for the affixes based on a language model. 
     
     
         10 . The system of  claim 9 , wherein the language model comprises at least one of: a feed-forward neural network with one or more non-linear hidden layers, or a log-linear language model. 
     
     
         11 . A computer-implemented method comprising:
 obtaining an input comprising textual data, wherein the textual data is segmentable into one or more words;   obtaining a list of affixes;   determining conditional probabilities for affixes in the list of affixes, wherein each conditional probability represents a value assigned to a respective affix, the value indicating a likelihood that adding the affix to the one or more words of the textual data results in a desirable domain name;   ranking the affixes based on the conditional probabilities to generate a ranked list of affixes; and   providing one or more domain name suggestions based on the ranked list of affixes.   
     
     
         12 . The method of  claim 11 , wherein the list of affixes comprises generic top-level domains (gTLDs), wherein the gTLDs are contextually relevant to the textual data. 
     
     
         13 . The method of  claim 11 , wherein determining conditional probabilities for affixes in the list of affixes comprises determining a plurality of conditional probabilities for an affix in the list of affixes. 
     
     
         14 . The method of  claim 13 , wherein determining a plurality of conditional probabilities for the affix in the list of affixes comprises two or more of:
 assigning a first conditional probability for adding the affix as a prefix to the one or more words of the textual data;   assigning a second conditional probability for adding the affix between two particular words in the textual data; or   assigning a third conditional probability for adding the affix as a suffix to the one or more words of the textual data.   
     
     
         15 . The method of  claim 11 , wherein determining conditional probabilities for affixes in the list of affixes comprises assigning conditional probabilities for the affixes based on a language model. 
     
     
         16 . A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause the processors to perform a method comprising:
 obtaining an input comprising textual data, wherein the textual data is segmentable into one or more words;   obtaining a list of affixes;   determining conditional probabilities for affixes in the list of affixes, wherein each conditional probability represents a value assigned to a respective affix, the value indicating a likelihood that adding the affix to the one or more words of the textual data results in a desirable domain name;   ranking the affixes based on the conditional probabilities to generate a ranked list of affixes; and   providing one or more domain name suggestions based on the ranked list of affixes.   
     
     
         17 . The non-transitory computer-readable medium of  claim 16 , wherein the list of affixes comprises generic top-level domains (gTLDs), wherein the gTLDs are contextually relevant to the textual data. 
     
     
         18 . The non-transitory computer-readable medium of  claim 16 , wherein determining conditional probabilities for affixes in the list of affixes comprises determining a plurality of conditional probabilities for an affix in the list of affixes. 
     
     
         19 . The non-transitory computer-readable medium of  claim 18 , wherein determining a plurality of conditional probabilities for the affix in the list of affixes comprises two or more of:
 assigning a first conditional probability for adding the affix as a prefix to the one or more words of the textual data;   assigning a second conditional probability for adding the affix between two particular words in the textual data; or   assigning a third conditional probability for adding the affix as a suffix to the one or more words of the textual data.   
     
     
         20 . The non-transitory computer-readable medium of  claim 16 , wherein determining conditional probabilities for affixes in the list of affixes comprises assigning conditional probabilities for the affixes based on a language model.