Vertical search expansion, disambiguation, and optimization of search queries
A system and method to facilitate expansion, disambiguation, and optimization of search queries over a network wherein an original query received from a user is parsed to obtain at least one query term. A plurality of keywords related contextually to one or more query terms are further retrieved from a database. Finally, a set of modified queries is generated, each modified query further comprising at least one query term and at least one retrieved keyword.
1. A method comprising:
parsing, in a computer, an original search query received from a user over a network through a query web page to obtain at least one query term;
retrieving a plurality of keywords from a database related contextually to a category of said query web page and said at least one query term;
generating, in a computer, a set of modified queries, each modified query comprising said at least one query term and at least one keyword of said plurality of keywords;
retrieving, in a computer, a plurality of advertising offers for each modified query and for said original query;
removing, in a computer, any advertising offer that is not related contextually to said category of said query web page; and
ranking, in a computer, the advertising offers not removed based on at least one predetermined parameter.
2. The method according to claim 1 , wherein each keyword and said at least one query term pertain to a common subject matter related to said page category.
3. The method according to claim 1 , further comprising:
selecting advertising offers related contextually to said at least one query term and said plurality of keywords; and
filtering said set of modified queries and said original query to generate a plurality of filtered queries, each filtered query corresponding to at least one selected advertising offer.
4. The method according to claim 1 , wherein:
said at least one predetermined parameter further comprises a “pay-per-click” (PPC) categorization parameter.
5. The method according to claim 1 , wherein:
said at least one predetermined parameter further comprises a combination between a “pay-per-click” (PPC) categorization parameter and a “click-through-rate” (CTR) categorization parameter.
6. The method according to claim 1 , wherein:
said at least one predetermined parameter further comprises a relevance categorization parameter.
7. A system comprising:
a server, comprising a processor and memory, for:
parsing an original search query received from a user over a network through a query web page to obtain at least one query term;
retrieving a plurality of keywords from a database related contextually to a category of said query web page and said at least one query term;
generating a set of modified queries, each modified query further comprising said at least one query term and at least one keyword of said plurality of keywords;
retrieving a plurality of advertising offers for each modified query and for said original query;
removing, in a computer, any advertising offer that is not related contextually to said category of said query web page; and
ranking, in a computer, the advertising offers not removed based on at least one predetermined parameter.
8. The system according to claim 7 , wherein each keyword and said at least one query term pertain to a common subject matter related to said page category.
9. The system according to claim 7 , said server further for:
selecting advertising offers related contextually to said at least one query term and said plurality of keywords; and
filtering said set of modified queries and said original query to generate a plurality of filtered queries, each filtered query corresponding to at least one selected advertising offer.
10. The system according to claim 7 , wherein:
said at least one predetermined parameter further comprises a “pay-per-click” (PPC) categorization parameter.
11. The system according to claim 7 , wherein:
said at least one predetermined parameter further comprises a combination between a “pay-per-click” (PPC) categorization parameter and a “click-through-rate” (CTR) categorization parameter.
12. A computer readable medium containing executable instructions, which, when executed in a processing system, cause the processing system to perform a method comprising:
parsing an original search query received from a user over a network through a query web page to obtain at least one query term;
retrieving a plurality of keywords from a database related contextually to a category of said query web page and said at least one query term;
generating a set of modified queries, each modified query further comprising said at least one query term and at least one keyword of said plurality of keywords;
retrieving a plurality of advertising offers for each modified query and for said original query;
removing, in a computer, any advertising offer that is not related contextually to said category of said query web page; and
ranking, in a computer, the advertising offers not removed based on at least one predetermined parameter.
13. The computer readable medium according to claim 12 , wherein each keyword and said at least one query term pertain to a common subject matter related to said page category.
14. The computer readable medium according to claim 12 , further comprising:
selecting advertising offers related contextually to said at least one query term and said plurality of keywords; and
filtering said set of modified queries and said original query to generate a plurality of filtered queries, each filtered query corresponding to at least one selected advertising offer.
15. The computer readable medium according to claim 12 , wherein:
said at least one predetermined parameter further comprises a “pay-per-click” (PPC) categorization parameter.
16. The computer readable medium according to claim 12 , wherein:
said at least one predetermined parameter further comprises a combination between a “pay-per-click” (PPC) categorization parameter and a “click-through-rate” (CTR) categorization parameter.
17. The computer readable medium according to claim 12 , wherein:
said at least one predetermined parameter further comprises a relevance categorization parameter.