Snippet generation and item description summarizer

Abstract

In various example embodiments, a system and method for a Target Language Engine are presented. The Target Language Engine augments a synonym list in a base dictionary of a target language with one or more historical search queries previously submitted to search one or more listings in listing data. The Target Language Engine identifies a compound word and a plurality of words present in the listing data that have a common meaning in the target language. Each word from the plurality of words is present in the compound word. The Target Language Engine causes a database to create an associative link between the portion of text and a word selected from at least one of the synonym list or the plurality of words.

What is claimed is: 
     
         1 . A system comprising:
 a processor; and   a memory coupled to the processor and storing instructions that, when executed by the processor, cause the system to perform operations comprising:
 receiving a search query from a mobile device that is mapped to a listing webpage for an item; 
 selecting one or more text portions from a plurality of text portions within the listing webpage based at least in part on a relevancy determination for the one or more text portions; 
 generating a listing snippet based at least in part on the one or more text portions; and 
 transmitting the listing snippet to the mobile device based at least in part on the search query. 
   
     
     
         2 . The system of  claim 1 , wherein the instructions to select the one or more text portions, when executed by the processor, further cause the system to perform operations comprising:
 selecting a first text portion of the one or more text portions based at least in part on a relevancy score of the first text portion satisfying a threshold relevancy score.   
     
     
         3 . The system of  claim 1 , the operations further comprising:
 comparing the plurality of text portions to a list of keywords;   identifying a subset of the plurality of text portions that includes one or more words from the list of keywords; and   selecting the one or more text portions from the subset of the plurality of text portions.   
     
     
         4 . The system of  claim 1 , the operations further comprising:
 comparing the plurality of text portions to a list of avoid words;   identifying a subset of the plurality of text portions that includes one or more words from the list of avoid words; and   refraining from selecting the one or more text portions from the subset of the plurality of text portions.   
     
     
         5 . The system of  claim 1 , the operations further comprising:
 comparing one or more text portions of the plurality of text portions to a list of words;   identifying a subset of words in the one or more text portions that include one or more words from the list of words;   removing, from the one or more text portions, the subset of words that include the one or more words from the list of words; and   generating the listing snippet based at least in part on removing the subset of words from the one or more text portions.   
     
     
         6 . The system of  claim 1 , the operations further comprising:
 scoring the relevancy determination of the one or more text portions based at least in part on a number of instances of one or more keywords present in each of the one or more text portions.   
     
     
         7 . The system of  claim 6 , wherein the instructions to generate the listing snippet, when executed by the processor, further cause the system to perform operations comprising:
 generating the listing snippet that includes a first text portion of the one or more text portions based at least in part on the first text portion corresponding to a threshold relevancy determination.   
     
     
         8 . A computer implemented method comprising:
 receiving, by at least one processor, a search query from a mobile device that is mapped to a listing webpage for an item;   selecting one or more text portions from a plurality of text portions within the listing webpage based at least in part on a relevancy determination for the one or more text portions;   generating a listing snippet based at least in part on the one or more text portions; and   transmitting the listing snippet to the mobile device based at least in part on the search query.   
     
     
         9 . The computer implemented method of  claim 8 , wherein selecting the one or more text portions comprises:
 selecting a first text portion of the one or more text portions based at least in part on a relevancy score of the first text portion satisfying a threshold relevancy score.   
     
     
         10 . The computer implemented method of  claim 8 , further comprising:
 comparing the plurality of text portions to a list of keywords;   identifying a subset of the plurality of text portions that includes one or more words from the list of keywords; and   selecting the one or more text portions from the subset of the plurality of text portions.   
     
     
         11 . The computer implemented method of  claim 8 , further comprising:
 comparing the plurality of text portions to a list of avoid words;   identifying a subset of the plurality of text portions that includes one or more words from the list of avoid words; and   refraining from selecting the one or more text portions from the subset of the plurality of text portions.   
     
     
         12 . The computer implemented method of  claim 8 , further comprising:
 comparing one or more text portions of the plurality of text portions to a list of words;   identifying a subset of words in the one or more text portions that include one or more words from the list of words;   removing, from the one or more text portions, the subset of words that include the one or more words from the list of words; and   generating the listing snippet based at least in part on removing the subset of words from the one or more text portions.   
     
     
         13 . The computer implemented method of  claim 8 , further comprising:
 scoring the relevancy determination of the one or more text portions based at least in part on a number of instances of one or more keywords present in each of the one or more text portions.   
     
     
         14 . The computer implemented method of  claim 13 , wherein generating the listing snippet comprises:
 generating the listing snippet that includes a first text portion of the one or more text portions based at least in part on the first text portion corresponding to a threshold relevancy determination.   
     
     
         15 . A non-transitory computer-readable medium storing instructions which, when executed by a processor, cause the processor to perform operations comprising:
 receiving a search query from a mobile device that is mapped to a listing webpage for an item;   selecting one or more text portions from a plurality of text portions within the listing webpage based at least in part on a relevancy determination for the one or more text portions;   generating a listing snippet based at least in part on the one or more text portions; and   transmitting the listing snippet to the mobile device based at least in part on the search query.   
     
     
         16 . The non-transitory computer-readable medium of  claim 15 , wherein the instructions, to select the one or more text portions, when executed, further cause the processor to perform operations comprising:
 selecting a first text portion of the one or more text portions based at least in part on a relevancy score of the first text portion satisfying a threshold relevancy score.   
     
     
         17 . The non-transitory computer-readable medium of  claim 15 , wherein the instructions, when executed, further cause the processor to perform operations comprising:
 comparing the plurality of text portions to a list of keywords;   identifying a subset of the plurality of text portions that include one or more words from the list of keywords; and   selecting the one or more text portions from the subset of the plurality of text portions.   
     
     
         18 . The non-transitory computer-readable medium of  claim 15 , wherein the instructions, when executed, further cause the processor to perform operations comprising:
 comparing the plurality of text portions to a list of avoid words;   identifying a subset of the plurality of text portions that include one or more words from the list of avoid words; and   refraining from selecting the one or more text portions from the subset of the plurality of text portions.   
     
     
         19 . The non-transitory computer-readable medium of  claim 15 , wherein the instructions, when executed, further cause the processor to perform operations comprising:
 comparing one or more text portions of the plurality of text portions to a list of words;   identifying a subset of words in the one or more text portions that include one or more words from the list of words;   removing, from the one or more text portions, the subset of words that include the one or more words from the list of words; and   generating the listing snippet based at least in part on removing the subset of words from the one or more text portions.   
     
     
         20 . The non-transitory computer-readable medium of  claim 15 , wherein the instructions, when executed, further cause the processor to perform operations comprising:
 scoring the relevancy determination of the one or more text portions based at least in part on a number of instances of one or more keywords present in each of the one or more text portions.