DISPLAYING CONCEPT-BASED TARGETED ADVERTISING
Methods and systems of the present invention allow for displaying suggested concept-based results. An exemplary method may comprise the steps of receiving targeted advertising information, determining from ontological calculations suggested keywords related to the concept of the targeted advertising information and displaying the suggested keywords.
1 . A method comprising the steps of:
A. receiving Targeted Advertising Information;
B. establishing from the Targeted Advertising Information an instance of an individual concept related to the Targeted Advertising Information;
C. identifying a class of concepts wherein one or more attributes of the class of concepts are related to one or more attributes of the individual concept;
D. establishing a plurality of relationships between the individual concept and each of the concepts within the class of concepts;
E. calculating a plurality of Suggested Keywords based on the concepts within the class of concepts most closely related to the individual concept; and
F. displaying the Suggested Keywords.
2 . The method of claim 1 wherein the relationships of step D are not based solely on one or more synonyms of the Targeted Advertising Information.
3 . The method of claim 1 wherein the relationships of step D are established based on Cluster Analysis.
4 . The method of claim 3 wherein the Cluster Analysis further comprises a Clustering Algorithm.
5 . The method of claim 3 wherein the Cluster Analysis further comprises a Fuzzy Cluster Analysis.
6 . The method of claim 3 wherein the Cluster Analysis further comprises Quality Threshold Clustering.
7 . The method of claim 3 wherein the Cluster Analysis further comprises Conceptual Clustering.
8 . A system comprising:
A. means for receiving Targeted Advertising Information:
B. means for establishing from the Targeted Advertising Information an instance of an individual concept related to the Targeted Advertising Information;
C. means for identifying a class of concepts wherein one or more attributes of the class of concepts are related to one or more attributes of the individual concept;
D. means for establishing a plurality of relationships between the individual concept and each of the concepts within the class of concepts;
E. means for calculating a plurality of Suggested Keywords based on the concepts within the class of concepts most closely related to the individual concept; and
F. means for displaying the plurality of Suggested Keywords.
9 . The system of claim 8 wherein the relationships of element D are not based solely on one or more synonyms of the Targeted Advertising Information.
10 . The system of claim 8 wherein the relationships of element D are established based on Cluster Analysis.
11 . The system of claim 10 wherein the Cluster Analysis further comprises a Clustering Algorithm.
12 . The system of claim 10 wherein the Cluster Analysis further comprises a Fuzzy Cluster Analysis.
13 . The system of claim 10 wherein the Cluster Analysis further comprises Quality Threshold Clustering.
14 . The method of claim 10 wherein the Cluster Analysis further comprises Conceptual Clustering.
15 . The system of claim 8 further comprising a Network, an Input Knowledge Agent, a Results Engine, an Ontology Language, a Clustering Algorithm, a Database, an Output Knowledge Agent or any combination thereof.
16 . A method comprising the steps of receiving Navigation Information relating to a Web Page, and upon navigating to the Web Page:
A. establishing from the Navigation Information an instance of an individual concept related to the Navigation Information;
B. identifying a class of concepts wherein one or more attributes of the class of concepts are related to one or more attributes of the individual concept;
C. establishing a plurality of relationships between the individual concept and each of the concepts within the class of concepts;
D. calculating a plurality of Customized Web Site Content based on the concepts within the class of concepts most closely related to the individual concept; and
E. displaying the Customized Web Site Content.
17 . The method of claim 16 wherein the relationships of step C are not based solely on one or more synonyms of the Navigation Information.
18 . The method of claim 16 wherein the relationships of step C are established based on Cluster Analysis.
19 . The method of claim 18 wherein the Cluster Analysis further comprises a Clustering Algorithm.
20 . The method of claim 18 wherein the Cluster Analysis further comprises a Fuzzy Cluster Analysis.
21 . The method of claim 18 wherein the Cluster Analysis further comprises a Quality Threshold Clustering.
22 . The method of claim 18 wherein the Cluster Analysis further comprises a Conceptual Clustering.
23 . A system comprising: means for receiving Navigation Information relating to a Web Page, and upon navigation to the Web Page further comprising:
A. means for establishing from the Navigation Information an instance of an individual concept related to the Navigation Information;
B. means for identifying a class of concepts wherein one or more attributes of the class of concepts are related to one or more attributes of the individual concept;
C. means for establishing a plurality of relationships between the individual concept and each of the concepts within the class of concepts;
D. means for calculating a plurality of Customized Web Site Content based on the concepts within the class of concepts most closely related to the individual concept; and
E. means for displaying the plurality of Customized Web Site Content.
24 . The system of claim 23 wherein the relationships of element C are not based solely on one or more synonyms of the Navigation Information.
25 . The system of claim 23 wherein the relationships of element C are established based on Cluster Analysis.
26 . The system of claim 25 wherein the Cluster Analysis further comprises a Clustering Algorithm.
27 . The system of claim 25 wherein the Cluster Analysis further comprises a Fuzzy Cluster Analysis.
28 . The system of claim 25 wherein the Cluster Analysis further comprises Quality Threshold Clustering.
29 . The method of claim 25 wherein the Cluster Analysis further comprises a Conceptual Clustering.
30 . The system of claim 23 further comprising a Network, an Input Knowledge Agent, a Results Engine, an Ontology Language, a Clustering Algorithm, a Database, an Output Knowledge Agent or any combination thereof.