Method and system for syntactic searching
The disclosure is directed at a method and system for improved search functionality. By using natural language processing (NLP), individual words in a search term may be parsed and then individually stored. The relationships between the individual words of the search term may also be stored such that when the search is repeated, the previous results may be retrieved and, if not, a more accurate search may be performed.
1. A method for syntactic searching for products available from merchants, the method comprising:
receiving search term comprising multiple individual words from user input at a user device;
parsing the individual words in the search term using natural language processing (NLP);
comparing the parsed individual words with words stored in a NLP database including a plurality of previously searched words from prior searches, and pre-populated words into the NLP database based on merchant product information, wherein the previously searched words and the pre-populated words each include relationship information associating selected ones of the previously searched words and the pre-populated words with each other and categorization information that categorizes each of the previously searched words and the pre-populated words;
causing display, at the user device, of search results based on comparison of words stored in the NLP database;
receiving, from the user device, a word change request from the user for a selected word among the individual words;
retrieving one or more alternate words associated with the selected word in a semantic tree;
displaying, at the user device, both the selected word and the one or more alternate words simultaneously and proximate to the selected word in a list of options for selection as a selected alternate word, the one or more alternate words including only words having a root word that is non-overlapping with respect to the selected word;
receiving an indication of the selected alternate word from among the one or more alternate words; and
updating the search results based on inclusion of the selected alternate word in the search term by employing machine learning to update the relationship information and the categorization information,
wherein parsing the individual words comprises categorizing the individual words as a selected one of group consisting of a root noun, a symbol, an adjective, a number, and a preposition, and
wherein retrieving the one or more alternate words comprises retrieving only words in a same category as the selected word.
2. The method of claim 1 wherein displaying search results comprises:
retrieving previously stored search results if parsed individual words are stored in the NLP database; and
displaying the previous search results.
3. The method of claim 1 wherein displaying search results comprises:
performing a search based on the search term if the parsed individual words are not stored in the NLP database to generate new search results; and
displaying the new search results.
4. The method of claim 3 further comprising:
storing the parsed individual words in the NLP database;
storing the new search results in the NLP database; and
associating the new search results with the parsed individual words.
5. The method of claim 1 further comprising:
storing the search term in the database.
6. The method of claim 1 wherein comparing the parsed individual words comprises:
grouping the parsed individual words; and
comparing the group of parsed individual words with the words in the NLP database.
7. The method of claim 6 wherein comparing the group of parsed individual words comprises:
comparing the parsed individual words with the words in the NLP database; and
determining if the words in the NLP database have relationships with other words in the NLP database associated with the group of parsed individual words.
8. The method of claim 7 wherein displaying search results comprises:
retrieving previously stored search results if the words in the NLP database have identical relationships with other words in the NLP database associated with the group of parsed individual words; and
displaying the previous search results.
9. The method of claim 7 wherein displaying search results comprises:
performing a new search based on the search term if the words in the NLP database do not have identical relationships with other words in the NLP database associated with the group of parsed individual words to generate new search results; and
displaying the new search results.
10. A non-transitory computer-readable medium having stored thereon computer executable instructions, that, if executed, cause a computer system to:
receive search term comprising multiple individual words from user input at a user device;
parse the individual words in the search term using natural language processing (NLP);
compare the parsed individual words with words stored in a NLP database including a plurality of previously searched words from prior searches, and pre-populated words into the NLP database based on merchant product information, wherein the previously searched words and the pre-populated words each include relationship information associating selected ones of the previously searched words and the pre-populated words with each other and categorization information that categorizes each of the previously searched words and the pre-populated words;
cause display, at the user device, of search results based on comparison of words stored in the NLP database;
receive, from the user device, a word change request from the user for a selected word among the individual words;
retrieve one or more alternate words associated with the selected word in a semantic tree;
display, at the user device, both the selected word and the one or more alternate words simultaneously and proximate to the selected word in a list of options for selection as a selected alternate word, the one or more alternate words including only words having a root word that is non-overlapping with respect to the selected word;
receive an indication of the selected alternate word from among the one or more alternate words; and
update the search results based on inclusion of the selected alternate word in the search term by employing machine learning to update the relationship information and the categorization information,
wherein parsing the individual words comprises categorizing the individual words as a selected one of group consisting of a root noun, a symbol, an adjective, a number, and a preposition, and
wherein retrieving the one or more alternate words comprises retrieving only words in a same category as the selected word.
11. The computer readable medium of claim 10 wherein the display of search results comprises:
retrieving previously stored search results if parsed individual words are stored in the NLP database; and
displaying the previous search results.
12. The computer readable medium of claim 10 wherein the display of search results comprises:
performing a search based on the search term if the parsed individual words are not stored in the NLP database to generate new search results; and
displaying the new search results.
13. The computer readable medium of claim 12 further comprising computer executable instructions, that, if executed, cause the computer system to:
store the parsed individual words in the NLP database;
store the new search results in the NLP database; and
associate the new search results with the parsed individual words.
14. The computer readable medium of claim 10 further comprising computer executable instructions, that, if executed, cause the computer system to:
store the search term in the database.
15. The method of claim 1 , wherein the word change request comprises a cursor hovering over the selected word.
16. The method of claim 1 , wherein the word change request comprises a user click on the selected word.
17. The computer readable medium of claim 10 , wherein the word change request comprises a cursor hovering over the selected word.
18. The computer readable medium of claim 10 , wherein the word change request comprises a user click on the selected word.