Method and system for task modeling of mobile phone applications

• US 8,776,009 B2
• Filed: 03/10/2010
• Issued: 07/08/2014
• Est. Priority Date: 03/12/2009
• Status: Expired due to Fees

• Current Assignee: Deutsche Telekom AG
• Original Assignee: Deutsche Telekom AG
• Inventors: Mimran, David, Shoval, Peretz, Henke, Katja, Dayan, Aviram, Tubi, Meytal, Shapira, Bracha, Levy, Meira, Glass, Gregor, Schneider, Lutz
• Primary Examiner(s): Dao, Thuy
• Assistant Examiner(s): Chowdhury, Ziaul A
• Application Number:
  US12/720,835
• Publication Number:
  US 20100235808A1
• Time in Patent Office: 1,581 Days
• Field of Search: None
• US Class Current: 717/104
• CPC Class Codes: G06F 11/3438 monitoring of user actions tracking the activity of the user H04L67/535

Abstract

A system for task modeling interactive sequential applications for one or more mobile devices has a software tool for defining a generic meta-model of the target applications. The generic meta-model has a static model of application components, and a dynamic model of identifiers of application screens and connections; a passive Task Model database for storing the generic meta-model for future reuse, which further comprises static instances of the generic meta-model specifically generated for a variety of mobile devices; a tracker module for real-time monitoring and creating unique identifier for each application'"'"'s screen visited by the user of the mobile device, wherein created identifiers are used for generating active models of the user actual use; and an active Task Model database for storing the active models, wherein data transferring and storing is minimized to screen identifier numbers.

Claims

1. A method for modeling interactive sequential applications for smart mobile devices, comprising the steps of:

a) generating in a central processing unit (CPU) a static model describing all goals of target applications using their screens, Screen Input Elements (SIEs), transitions between screens, sub-goals and the links between them;

b) building in said CPU a dynamic model based on said static model by tracking the use of the application screens over an actual device while using an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models;

c) creating instances of said static and dynamic models specifically generated for a variety of devices;

d) storing said static and dynamic models with their instances into a passive Task Model database, being in data communication with said CPU;

e) downloading relevant passive Task Models to user'"'"'s device according its type and the application supported by said user'"'"'s device;

f) tracking in real-time user'"'"'s actions during user-system interactions and generating a unique identifier for each application'"'"'s screen that is visited by the user of said mobile device by choosing an identifier that matches a signature of each application'"'"'s screen, wherein created identifiers are used for generating an active model of the user'"'"'s actual usage;

g) storing said tracked model into an active Task Model database being in data communication with said CPU; and

h) comparing said active Task Model to said passive Task Model and generating usage patterns for said user;

wherein the static and dynamic models are in the form of an Entity Relationship Diagram (ERD), and implemented in a relational database.

2. The method according to claim 1, further comprising verifying the screen identifier before storing in active Task Model database for validating the tracking.

3. The method according to claim 1, further comprising offering the client real-time help, marketing and content determined by the provider, based on the tracked data and relevant passive Task Models downloaded to client'"'"'s device.

4. The method according to claim 1, further comprising analyzing data by comparing said passive and active databases, for generating an output database that comprises usage patterns, error patterns, user'"'"'s intention prediction, market trends, and usability hotspots (problems) in addition to graphs and reports for helping providers realizing customers'"'"' activities and behavior.

5. The method according to claim 1, wherein each of the model entities is associated with a unique primary identifier and with a base identifier, said base identifier being derivable from a parent entity when said parent entity is reused by a given model entity and being identical to said primary identifier when said given model entity is a parent entity.

6. The method according to claim 5, wherein the parent entity is changed when reused by the given model entity.

7. The method according to claim 6, wherein data of the parent entity is overridden by the given model entity.

8. A system for task modeling interactive sequential applications for one or more mobile devices, comprising:

a) a central processing unit (CPU) having a software tool for defining a generic meta-model of the target applications, wherein said generic meta-model consists of a static model of application components, and a dynamic model of identifiers of application screens and connections that are based on an inheritance mechanism whereby model entities having a parent-child relationship are reusable in different models;

b) a passive Task Model database, being in data communication with said CPU, for storing said generic meta-model for future reuse, which further comprises static instances of the generic meta-model specifically generated for a variety of mobile devices;

c) a tracker module in said processing unit for;

c1) real-time tracking and monitoring user'"'"'s actions during user-system interactions and creating a screen unique identifier for each application'"'"'s screen visited by the user of said mobile device by choosing an identifier that matches a signature of each application'"'"'s screen, wherein created identifiers are used for generating active models of the user'"'"'s actual usage; and

c2) generating a unique identifier for each captured screen that is presented to said user;

d) an active Task Model database, being in data communication with said processing unit, for storing said active model, wherein data transferring and storing is minimized to screen unique identifier and;

e) an analyzer for comparing said active Task Model to said passive Task Model and for generating usage patterns for said user.

9. The system according to claim 8, wherein the mobile device is a smart mobile phone.

10. The system according to claim 8, wherein the screen identifier number is the screen signature.

11. The system according to claim 8, wherein the mobile device further comprises a real-time recommender engine, for offering the client real-time help, marketing and content determined by the provider.

12. The system according to claim 11, wherein the real-time recommendation is based on the tracked data and relevant passive Task Models downloaded to the mobile device.

13. The system according to claim 8, further comprising an analyzer that receives data from both the passive and active databases and compares said databases for generating an output database.

14. The system according to claim 13, wherein the output database comprises usage patterns, error patterns, user'"'"'s intention prediction, market trends, and usability problems, in addition to graphs and reports for helping providers realizing customers'"'"' activities and behavior.

15. The system according to claim 8, wherein each of the model entities is associated with a unique primary identifier and with a base identifier, said base identifier being derivable from a parent entity when said parent entity is reused by a given model entity and being identical to said primary identifier when said given model entity is a parent entity.