Purpose-based adaptive rendering
View Patent ↗The present invention provides an automated interactive system that enables an author to build applications that handle complex consumer-merchant interactions. The author designs content components and application rules that are interpreted by the system dynamically, at runtime, to generate and deliver to users personalized HTML web pages, including client-side objects that track user behavior and enhance users' interaction with the application. Such rules dynamically adapt the author's goals to the appropriate users at the appropriate time, thereby simulating the dialogue between users and human salespersons/customer service personnel in the context of an automated interactive system.
1. A method for adaptively rendering, to users of a computer network application, a plurality of content pages generated dynamically from a plurality of content objects compiled by an author of the application, the method comprising the following steps:
(a) compiling a user database from individual and aggregate user profile data and observed user behavioral data;
(b) compiling a content database from a hierarchy of content objects, including primitive objects, content elements containing a plurality of primitive objects, content pages containing a plurality of content elements and primitive objects, and user scenarios containing a plurality of content pages;
(c) facilitating the author's creation of a rule effecting author-defined scenarios, based at least in part on dynamic data from the user database, that dynamically selects subsets of users to receive subsets of content objects, the rule having a parameter that is resolved only dynamically at runtime, wherein a navigation map initially defines the set of possible paths among the various web pages within the author-defined scenarios; and
(d) dynamically interpreting the rule to render content pages, the content pages including a first subset of content objects delivered over the network to a first subset of users, and a second subset of content objects delivered over the network to a second subset of users, wherein a plurality of templates are selected dynamically based on the interpretation of the rule to determine the size and location of the dynamically selected content objects.
2. The method of claim 1 wherein the parameter is resolved based at least in part upon aggregate observed user behavior.
3. The method of claim 2 further comprising dynamically selecting a user scenario based on the aggregate observed user behavior, wherein the user scenario comprises a plurality of linked content pages and the aggregate observed user behavior comprises a percentage of users that reached the end of the user scenario.
4. The method of claim 3 wherein the user scenario comprises two or more alternative paths to reach the end of the user scenario and the aggregate observed user behavior comprises the percentage of users that reached the end of the scenario from each of the two or more alternative paths.
5. The method of claim 3 wherein the aggregate observed user behavior comprises the percentage of users that reached the end of the user scenario within a certain number of steps.
6. The method of claim 1 wherein subsequent content pages are pre-fetched and delivered to a user's web browser while the user is viewing a current content page, and such pre-fetching is based on the user's profile and observed behavioral data.
7. A system adaptively rendering, to users of a computer network application, a plurality of content pages generated dynamically from a plurality of content objects compiled by an author of the application, the system comprising:
a processor comprising:
(a) a user database compiling individual and aggregate user profile data and observed user behavioral data;
(b) a content database compiling a hierarchy of content objects, including primitive objects, content elements containing a plurality of primitive objects, content pages containing a plurality of content elements and primitive objects, and user scenarios containing a plurality of content pages;
(c) an application builder facilitating the author's creation of a rule effecting author-defined scenarios based at least in part on dynamic data from the user database, that dynamically selects subsets of users to receive subsets of content objects, the rule having a parameter that is resolved only dynamically at runtime, wherein a navigation map initially defines the set of possible paths among the various pages within the author-defined scenarios; and
(d) a dynamic content composition engine for dynamically interpreting the rule to render content pages, the content pages including a first subset of content objects delivered over the network to a first subset of users, and a second subset of content objects delivered over the network to a second subset of users, wherein a plurality of templates are selected dynamically based on the interpretation of the rule to determine the size and location of the dynamically selected content objects.
8. The system of claim 7 wherein the parameter is resolved based at least in part upon aggregate observed user behavior.
9. The system of claim 8 further comprising dynamically selecting a user scenario based on the aggregate observed user behavior, wherein the user scenario comprises a plurality of linked content pages and the aggregate observed user behavior comprises a percentage of users that reached the end of the user scenario.
10. The system of claim 9 wherein the user scenario comprises two or more alternative paths to reach the end of the user scenario and the aggregate observed user behavior comprises the percentage of users that reached the end of the scenario from each of the two or more alternative paths.
11. The system of claim 9 wherein the aggregate observed user behavior comprises the percentage of users that reached the end of the user scenario within a certain number of steps.
12. The system of claim 7 wherein subsequent content pages are pre-fetched and delivered to a user's web browser while the user is viewing a current content page, and such pre-fetching is based on the user's profile and observed behavioral data.