Automated story model collaboration system
In the various example embodiments disclosed herein, a best next action is recommended by a user's model by establishing from user inputs a personally relevant narrative context; establishing a narrative context using a Story Object Hierarchy; constructing values for user attributes and goals based on the Story Object Hierarchy; determining from the goals a user's envisioned story; optimizing actions to advance the user towards the user's envisioned story; optimizing communication of the optimized actions to reflect the constituents of the Story Object Hierarchy most likely to advance the user towards user's envisioned story; receiving new user input after communicating the optimized actions to the user; evaluating user progress towards the user's envisioned story; and recommending for the user a best next action for their personally relevant narrative context.
1 . A method comprising: processing a set of datastreams associated with a user, wherein the set of datastreams is continuously received in real-time, and wherein the set of datastreams corresponds to inputs associated with the user, other users, and different user devices; transforming the set of datastreams into story model inputs with at least one intermediate representation having at least one universal data type, wherein the story model inputs include a set of context-tagged scores generated using a classifier trained on validated reference data, and a set of context-tagged mentions generated using an extractor trained on validated models; translating the story model inputs into a set of story model objects, wherein the set of story model objects defines data structure dependencies and relationships on different story data types; processing the set of story model objects through a user story model to generate a user current story, wherein the user current story includes a profile of user attributes expressed in terms of different values corresponding to the different story data types, and wherein the user current story provides a representation of the user at a particular moment in time; processing the user current story through an envisioned story generation model to generate a user envisioned story, wherein the user envisioned story includes a set of target values corresponding to the different story data types; processing the user current story and the user envisioned story through an actualizer to identify one or more story model objects from the set of story model objects and that correspond to a narrative segment executable to cause a transition from the user current story to the user envisioned story; executing the narrative segment, wherein when the narrative segment is executed, new datastreams associated with the user are logged to determine an effectiveness of the narrative segment in achieving the user envisioned story; updating the user story model and the actualizer according to the effectiveness of the narrative segment in achieving the user envisioned story; and processing the new datastreams through the updated user story model and the updated actualizer to generate new user envisioned stories and new narrative segments corresponding to the new user envisioned stories.
2 . The method of claim 1 , wherein the set of datastreams is of a type from a group consisting of: video data, image data, audio data, text data, and simple data.
3 . The method of claim 1 , wherein processing the set of datastreams further comprises: performing automated feature extraction and datastream type specific processing on the set of datastreams.
4 . The method of claim 1 , wherein translating the story model inputs into the set of story model objects further comprises: transforming the story model inputs into tensor representations corresponding to a datatype of the set of datastreams.
5 . The method of claim 1 , further comprising: transforming the at least one intermediate representation of the story model inputs into predicates, subject-verb-objects (SVOs), and scores.
6 . The method of claim 1 , wherein each story model object from the set of story model objects includes an executable code portion and a story data type portion.
7 . The method of claim 1 , further comprising: determining a predicted impact that the one or more story model objects will have on a story object hierarchy associated with the other users; and updating the actualizer according to the predicted impact.
8 . The method of claim 1 , further comprising: determining a predicted impact that the one or more story model objects will have in transitioning the user current story to the user envisioned story; and updating the user story model and the actualizer according to a difference between the predicted impact and the effectiveness of the narrative segment.
9 . The method of claim 1 , wherein the actualizer identifies the one or more story model objects based on a predicted impact that the one or more story model objects will have in achieving the user envisioned story.
10 . The method of claim 1 , wherein executing the narrative segment further comprises: communicating a request for input required to continue execution of the narrative segment, wherein the request for input is routed to the user via a narrative template; and routing a response to the request for input through the narrative template.
11 . The method of claim 1 , further comprising: communicating a natural language output of the narrative segment to the user.
12 . The method of claim 1 , further comprising: performing a user story model collaboration between the user and different users through a networked data communication between the actualizer and different actualizers associated with the different users across a story model collaboration network.
13 . The method of claim 1 , further comprising: transmitting, through the actualizer, a request for resource resolution as a networked data communication to a different actualizer associated with a different user across a story model collaboration network.
14 . The method of claim 1 , further comprising: receiving a networked data communication from a different actualizer associated with a different user across a story model collaboration network, wherein the networked data communication includes a request for resource resolution corresponding to an executable action; and processing the request through the actualizer to generate a response, wherein the response is generated according to an impact of the resource resolution on the user envisioned story.
15 . The method of claim 1 , further comprising: determining a level of drift corresponding to a deviation between the user current story and the user envisioned story; and adjusting the narrative segment to reduce the level of drift.
16 . The method of claim 1 , further comprising: determining a level of drift corresponding to a deviation between the user current story and the user envisioned story; exchanging information between the user story model and a different user story model associated with a different user, wherein the information is exchanged in a user story model collaboration across a story model collaboration network; and using the user story model collaboration to adjust the narrative segment to reduce the level of drift.
17 . The method of claim 1 , wherein the narrative segment includes a contract, wherein the contract defines a sequence of deliverable exchanges amongst a user role corresponding to the user and other user roles corresponding to the other users; and wherein the narrative segment identifies and resolves conflicts that impact the contract and role performance associated with the user role and the other user roles as the new datastreams are logged.
18 . The method of claim 1 , wherein: generating the user envisioned story further comprises defining a set of goals based on a user role corresponding to the user, other user roles corresponding to the other users, and a set of contracts; and determining the effectiveness of the narrative segment further comprises determining an importance of the user role, the other user roles, and the set of contracts according to actions performed during execution of the narrative segment.
19 . The method of claim 1 , wherein the different values and the set of target values further correspond to user roles, contracts, and deliverables according to completeness, importance, satisfaction, and dissatisfaction measures.
20 . The method of claim 1 , further comprising: performing a negotiation corresponding to different contracts required by the user and the other users to fulfill different goal roles, wherein the negotiation is performed through a networked data communication between the actualizer and different actualizers associated with the other users across a story model collaboration network.
21 . The method of claim 1 , wherein the different values and the set of target values include at least one value corresponding to contracts and contract constituents.
22 . The method of claim 1 , wherein the narrative segment is executed to propagate new contracts to advance roles through planned deliverables within pairwise role contexts.