Abstract: The method and system of merges user-supplied electronic content with relevant ads based upon relevancy factors discerned form the ads and the content. Further, profiles and session histories of user-visitors are monitored and ad relevancy factors discerned form the profiles and session histories are employed to obtain user-relevant ads. The content relevant ads and user relevant ads are inserted into a preformed web page in addition to the user-supplied content. A revenue splitting module shares the ad referral or sales revenue from the click throughs to advertiser designated web sites. The relevancy factors relate to one or more of the supplied content, the user who uploaded the content, the user profile (previously input by the user), current session history, past session history, the user-group profiles and any user referral source. A comparator matches relevancy factors and ads. Ad selection by category, hierarchical or orthogonal match and high pay referral fees.

Abstract: The invention calculates, allocates and pays a Content-Provider-CP for online content with an adaptive value calculator, a payment processor computer, memory and associated web-server. The CP allocation in one system is based upon User-CP centric actions or characteristics (A-C); Content centric A-C; Content Performance centric characteristics; and Viewer centric A-C. A compiler registers Users-CPs. An uploader delivers CP content to the web-server. A tracking module monitors views and acclamations on uploaded content. A revenue tracker accounts for revenue sources on the web-server. An allocation processor calculates CP payments. Metric examples are: CP centric (famous CP or frequent CP poster); Content centric (geographically relevant or trending topic); Performance centric (views on published content); Viewer centric (comments by famous critic). A payment module pays the CP through a banking system. Metrics are time-based temporal functions.

Abstract: The invention calculates, allocates and pays a Content-Provider-CP for online content with an adaptive value calculator, a payment processor computer, memory and associated web-server. The CP allocation in one system is based upon User-CP centric actions or characteristics (A-C); Content centric A-C; Content Performance centric characteristics; and Viewer centric A-C. A compiler registers Users-CPs. An uploader delivers CP content to the web-server. A tracking module monitors views and acclamations on uploaded content. A revenue tracker accounts for revenue sources on the web-server. An allocation processor calculates CP payments. Metric examples are: CP centric (famous CP or frequent CP poster); Content centric (geographically relevant or trending topic); Performance centric (views on published content); Viewer centric (comments by famous critic). A payment module pays the CP through a banking system. Metrics are time-based temporal functions.

Abstract: The computer-based method and system shares revenue with a content provider and registered users. A web page has supplied electronic content and ads with displays and hyperlinks to a corresponding advertiser designated web site. Associated sales referral fees are tracked based upon user click throughs. The content provider is incentivized because the system shares the associated sales referral fees with him based upon factors such as frequency of posting content, quality rankings by users, gross value referral fees, and page user-visitors. Registered user-visitors are incentivized by providing each with N quality ranking tokens and by sharing the referral fees with users who post tokens on content. The QA ranking formula accounts for the quantity of posted tokens, the sequential order of posting, the number of user-visitors, and the referral fee to the content provider. The fees are paid to debit card, credit card, or cell phone account payment processors.

Abstract: The computer-based method and system shares revenue with a content provider and registered users. A web page has supplied electronic content and ads with displays and hyperlinks to a corresponding advertiser designated web site. Associated sales referral fees are tracked based upon user click throughs. The content provider is incentivized because the system shares the associated sales referral fees with him based upon factors such as frequency of posting content, quality rankings by users, gross value referral fees, and page user-visitors. Registered user-visitors are incentivized by providing each with N quality ranking tokens and by sharing the referral fees with users who post tokens on content. The QA ranking formula accounts for the quantity of posted tokens, the sequential order of posting, the number of user-visitors, and the referral fee to the content provider. The fees are paid to debit card, credit card, or cell phone account payment processors.

Abstract: The method and system of merges user-supplied electronic content with relevant ads based upon relevancy factors discerned form the ads and the content. Further, profiles and session histories of user-visitors are monitored and ad relevancy factors discerned form the profiles and session histories are employed to obtain user-relevant ads. The content relevant ads and user relevant ads are inserted into a preformed web page in addition to the user-supplied content. A revenue splitting module shares the ad referral or sales revenue from the click throughs to advertiser designated web sites. The relevancy factors relate to one or more of the supplied content, the user who uploaded the content, the user profile (previously input by the user), current session history, past session history, the user-group profiles and any user referral source. A comparator matches relevancy factors and ads. Ad selection by category, hierarchical or orthogonal match and high pay referral fees.

Abstract: The computer-based method and system shares revenue with a content provider and registered users. A web page has supplied electronic content and ads with displays and hyperlinks to a corresponding advertiser designated web site. Associated sales referral fees are tracked based upon user click throughs. The content provider is incentivized because the system shares the associated sales referral fees with him based upon factors such as frequency of posting content, quality rankings by users, gross value referral fees, and page user-visitors. Registered user-visitors are incentivized by providing each with N quality ranking tokens and by sharing the referral fees with users who post tokens on content. The QA ranking formula accounts for the quantity of posted tokens, the sequential order of posting, the number of user-visitors, and the referral fee to the content provider. The fees are paid to debit card, credit card, or cell phone account payment processors.