Generating keywords by associative context with input words
Systems and methods are provided for accessing a plurality of inventory item listings accessible over a network, wherein each of the plurality of inventory item listings includes one or more text strings, and creating inventory word vectors for at least some of the text strings of the plurality of inventory item listings. The systems and methods further provide for receiving a user input including an input word, wherein the user input is input by a user to access a primary media content, creating an input word vector for the input word, calculating cosine similarities between the input word vector and the inventory word vectors, and analyzing the calculated cosine similarities to determine one or more keywords from the one or more text strings, wherein the one or more keywords are from the text strings having inventory word vectors with the highest cosine similarities to the input word vector.
1. A computer-implemented method comprising:
receiving, from a client device, a user input that comprises a first text string;
calculating, by one or more processors, a plurality of similarities between the first text string and a second text string of a plurality of text strings;
reducing the first text string and the second text string;
creating a first word vector from the first reduced text string with an open source tool;
creating a second word vector from the second reduced text string with the open source tool;
identifying, by the one or more processors, a word from the first word vector or the second word vector; and
outputting a search result comprising information associated with the word.
2. The computer-implemented method of claim 1 , further comprising sorting, by the one or more processors, the plurality of similarities between the first text string and the second text string of the plurality of text strings.
3. The computer-implemented method of claim 1 , further comprising
calculating a first similarity of the plurality of similarities based at least in part on the first word vector and the second word vector.
4. The computer-implemented method of claim 3 , wherein creating the first word vector further comprises:
identifying one or more special characters in the first text string; and
creating the first word vector that excludes the one or more special characters.
5. The computer-implemented method of claim 1 , further comprising selecting an advertisement based at least in part on identifying the word, wherein outputting the search result comprises outputting the advertisement.
6. The computer-implemented method of claim 1 , wherein outputting the search result further comprises outputting the search result comprising a media content.
7. The computer-implemented method of claim 1 , wherein outputting the search result further comprises outputting the search result comprising one or more listings from an online marketplace.
8. A system, comprising:
at least one processor; and
a memory device storing instructions that, when executed by the at least one processor, cause the system to perform operations comprising:
receiving, from a client device, a user input that comprises a first text string;
calculating a plurality of similarities between the first text string and a second text string of a plurality of text strings;
reducing the first text string and the second text string;
creating a first word vector from the first reduced text string with an open source tool;
creating a second word vector from the second reduced text string with the open source tool;
identifying a word from the first word vector or the second word vector; and
outputting a search result comprising information associated with the word.
9. The system of claim 8 , wherein the instructions are further executable to perform operations comprising sorting the plurality of similarities between the first text string and the second text string of the plurality of text strings.
10. The system of claim 8 , wherein the instructions are further executable to perform operations comprising
calculating a first similarity of the plurality of similarities based at least in part on the first word vector and the second word vector.
11. The system of claim 10 , wherein the instructions to create the first word vector are further executable to perform operations comprising:
identifying one or more special characters in the first text string; and
creating the first word vector that excludes the one or more special characters.
12. The system of claim 8 , wherein the instructions are further executable to perform operations comprising selecting an advertisement based at least in part on identifying the word, wherein outputting the search result comprises outputting the advertisement.
13. The system of claim 8 , wherein the instructions to output the search result are further executable to perform operations comprising outputting the search result comprising a media content.
14. The system of claim 8 , wherein the instructions to output the search result are further executable to perform operations comprising outputting the search result comprising one or more listings from an online marketplace.
15. A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause a machine to perform operations comprising:
receiving, from a client device, a user input that comprises a first text string;
calculating a plurality of similarities between the first text string and a second text string of a plurality of text strings;
reducing the first text string and the second text string;
creating a first word vector from the first reduced text string with an open source tool;
creating a second word vector from the second reduced text string with the open source tool;
identifying a word from the first word vector or the second word vector; and
outputting a search result comprising information associated with the word.
16. The non-transitory computer-readable medium of claim 15 , wherein the instructions are further executable to cause the machine to perform operations comprising sorting the plurality of similarities between the first text string and the second text string of the plurality of text strings.
17. The non-transitory computer-readable medium of claim 15 , wherein the instructions are further executable to cause the machine to perform operations comprising:
calculating a first similarity of the plurality of similarities based at least in part on the first word vector and the second word vector and wherein the instructions to create the first word vector are further executable to cause the machine to perform operations comprising:
identifying one or more special characters in the first text string; and
creating the first word vector that excludes the one or more special characters.
18. The non-transitory computer-readable medium of claim 15 , wherein the instructions are further executable to cause the machine to perform operations comprising selecting an advertisement based at least in part on identifying the word, wherein outputting the search result comprises outputting the advertisement.
19. The non-transitory computer-readable medium of claim 15 , wherein the instructions to output the search result are further executable to cause the machine to perform operations comprising outputting the search result comprising a media content.
20. The non-transitory computer-readable medium of claim 15 , wherein the instructions to output the search result are further executable to cause the machine to perform operations comprising outputting the search result comprising one or more listings from an online marketplace.