초록 ▼

A system and method to facilitate classification and storage of events in a network are described. An event and associated content information are received from an entity over a network. The content information is further analyzed to determine one or more themes representing subject matter related t

A system and method to facilitate classification and storage of events in a network are described. An event and associated content information are received from an entity over a network. The content information is further analyzed to determine one or more themes representing subject matter related to the content information. The event is further classified according to the themes into one or more corresponding categories. Finally, the event is stored into one or more corresponding databases of a data storage module according to the one or more corresponding categories.

대표청구항 ▼

1. A computer-implemented method comprising: receiving, by a processor, a web page and web page content information associated with the web page; classifying, by a processor, said web page content information to a content category of a hierarchical content taxonomy based on a theme of the web page c

1. A computer-implemented method comprising: receiving, by a processor, a web page and web page content information associated with the web page; classifying, by a processor, said web page content information to a content category of a hierarchical content taxonomy based on a theme of the web page content information;receiving, by a processor, an advertisement and an advertisement content associated with the advertisement;classifying, by a processor, said advertisement to an advertisement category of a hierarchical advertising taxonomy based on a theme of the advertisement content;generating, by a processor, a mapping probability table to associate the content category with the advertisement category, the mapping probability table comprising: a match between the theme of the web page content information and the advertisement, wherein the match is based on a logical association of the content category and the advertising category and not upon the web page content information alone; andmapping information comprising at least one probability score corresponding to a likelihood, based on the match, that a viewer with an interest in the content category has an interest in the advertising category; and storing, by a processor, the mapping probability table, the content taxonomy, andthe advertising taxonomy. 2. The computer-implemented method according to claim 1, wherein the theme of the web page content information is contextually related to said web page content information. 3. The computer-implemented method according to claim 1, wherein said web page and said associated web page content information are received over a network. 4. The computer-implemented method according to claim 1, further comprising: parsing said web page and said web page content information; andextracting said theme of the web page content information. 5. The computer-implemented method according to claim 1, wherein the advertisement and the associated advertisement content information are received over a network. 6. The computer-implemented method according to claim 1, further comprising: parsing said advertisement and said advertisement content information; andextracting said theme of the advertisement content information. 7. A computer system comprising: at least one web server, comprising at least one processor and memory, that is configured to receive a web page and web page content information associated with the web page and to receive an advertisement and an advertisement content associated with said advertisement; a processing platform, comprising at least one processor and memory, coupled to said at least one web server, the processing platform being configured to: classify said web page content information of said web page to a content category of a hierarchical content taxonomy based on a theme of the web page content information,classify said advertisement to an advertisement category of a hierarchical advertising taxonomy based on a theme of the advertisement content,generate a mapping probability table to associate the content category with the advertising category based on the theme of the web page content information, the mapping probability table comprising:a match between the theme of the web page content information and the advertisement, wherein the match is based on a logical association of the content category and the advertising category and not upon the web page content information alone; andmapping information comprising at least one probability score corresponding to a likelihood, based on the match, that a viewer with an interest in the content category has an interest in the advertising category. 8. The system according to claim 7, wherein the theme of the web page content information is contextually related to said web page content information. 9. The system according to claim 8, wherein said processing platform is further configured to parse said web page and said web page content information and to extract said theme of the web page content information. 10. The system according to claim 7, wherein said advertisement and said advertisement content information are received over a network. 11. The system according to claim 10, wherein said processing platform is further configured to parse said advertisement and said advertisement content information and extracts said theme of the advertisement content information. 12. A non-transitory computer readable storage medium comprising executable instructions, the executable instructions to direct a processor to perform acts of: receiving a web page and web page content information associated with the webpage;classifying said web page content information to a content category of a hierarchical content taxonomy based on a theme of the web page content information;receiving an advertisement and an advertisement content associated with the advertisement; classifying said advertisement to an advertisement category of a hierarchical advertising taxonomy based on a theme of the advertisement content; generating a mapping probability table to associate the content category with the advertising category, the mapping probability table comprising:a match between the theme of the web page content information and the advertisement, wherein the match is based on a logical association of the content category and the advertising category and not upon the web page content information alone; andmapping information comprising at least one probability score corresponding to a likelihood, based on the match, that a viewer with an interest in the content category has an interest in the advertising category. 13. The non-transitory computer readable storage medium according to claim 12, wherein the theme is contextually related to said content information. 14. The non-transitory computer readable storage medium according to claim 12, wherein: said web page and said web page content information are received over a network; andthe executable instructions are configured to direct a processor to further perform acts of: parsing said web page and said content information; andextracting said theme. 15. The non-transitory computer readable storage medium according to claim 12, wherein said advertisement and said advertisement content information are received over a network. 16. The non-transitory computer readable medium according to claim 15, wherein the executable instructions are configured to direct a processor to further perform acts of: parsing said advertisement and said advertisement content information; andextracting said theme of the advertisement content information.