System and method for intermachine markup language communications

• US 20140089241A1
• Filed: 08/19/2013
• Published: 03/27/2014
• Est. Priority Date: 02/01/1999
• Status: Abandoned Application

• Current Assignee: Hoffberg Family Trust 2, Blanding Hovenweep LLC (Intellectual Ventures LLC), STEVEN M. HOFFBERG 2004-1 GRAT
• Original Assignee: Hoffberg Family Trust 2
• Inventors: Hoffberg, Steven M., Hoffberg-Borghesani, Linda I.
• Application Number:
  US13/970,102
• Publication Number:
  US 20140089241A1
• Time in Patent Office: Days
• US Class Current: 706/14
• CPC Class Codes: G05B 15/02 electric
• CPC Class Codes: G06F 3/048 Interaction techniques based on graphical user interfaces [GUI]
• CPC Class Codes: G06N 20/00 Machine learning
• CPC Class Codes: G06N 5/025 Extracting rules from data
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0248 Avoiding fraud
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0267 Wireless devices
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: H04N 2005/91328 the copy protection signal being a copy management signal, e.g. a copy generation management signal [CGMS]
• CPC Class Codes: H04N 2005/91364 the video signal being scrambled
• CPC Class Codes: H04N 21/4131 home appliance, e.g. lighting, air conditioning system, metering devices home automation data switching networks exchanging configuration information on appliance services H04L12/2807
• CPC Class Codes: H04N 21/42201 biosensors, e.g. heat sensor for presence detection, EEG sensors or any limb activity sensors worn by the user input arrangements for interaction with the human body based on nervous system activity detection G06F3/015
• CPC Class Codes: H04N 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/47 End-user applications
• CPC Class Codes: H04N 5/782 on tape
• CPC Class Codes: H04N 5/913 for scrambling ; for copy protection

Abstract

A system, comprising a network interface, an additional data communications interface, and processor for supporting a control interface communicated through the network interface according to an intermachine markup language protocol, for controlling the network interface and the additional data communications interface.

Claims

1. A human interface system, comprising:

a user input, receiving user instructions for control of a system;

an intelligent analysis system, monitoring said user instructions, to determine a user instruction pattern;

a feedback system, presenting an output representing the determined user instruction pattern, and receiving modification input from the user representing a concurrence with said determined user instruction pattern, data relating to said modification input being provided to said intelligent analysis system for alteration of said determined user instruction pattern based on said modification input; and

an operative system, presenting surrogate user instructions for control of the system based on said determined user instruction pattern.

2. The human interface system according to claim 1, further comprising:

a database engine, for retrieving information from a database, said database including information having varying degrees of relevance to said determined user instruction pattern, said determined user instruction pattern comprising a query for said database engine for selectively retrieving information having a high degree of relevance to said determined user instruction.

3. The human interface system according to claim 1, further comprising:

an input for monitoring an activity of said operative system; and

;

a correlator, for correlating said monitored activity with said determined user instruction, producing an output indicative of a degree of relation between said determined user activity and said monitored activity.

4. A human interface system, comprising:

a user input, receiving user instructions for control of a system;

an intelligent analysis system, monitoring said user instructions, to determine a user instruction pattern;

a feedback system, presenting an output representing the determined user instruction pattern, and receiving modification input from the user representing a concurrence with said determined user instruction pattern, data relating to said modification input being provided to said intelligent analysis system for alteration of said determined user instruction pattern based on said modification input;

an operative system, presenting surrogate user instructions for control of the system based on said determined user instruction pattern.

5. The human interface system according to claim 4, further comprising:

a database engine, for retrieving information from a database, said database including information having varying degrees of relevance to said determined user instruction pattern, said determined user instruction pattern comprising a query for said database engine for selectively retrieving information having a high degree of relevance to said determined user instruction.

6. The human interface system according to claim 4, further comprising:

an input for monitoring an activity of said operative system; and

;

a correlator, for correlating said monitored activity with said determined user instruction, producing an output indicative of a degree of relation between said determined user activity and said monitored activity.

7. A method, comprising the steps of:

receiving data describing an user attribute;

receiving a content data stream, and extracting from the content data stream information describing a plurality of program options;

processing the data describing a user attribute and the information describing a plurality of program options to determine a likely user preference;

selectively processing a program option based on said likely user preference.

8. The method according to claim 7, wherein:

said method is used by a terminal for a television program delivery system for suggesting programs to users for display on a television using program control information and user specific data;

said step of receiving data describing an user attribute comprises gathering user specific data to be used in selecting programs, and storing the gathered user specific data;

said step of receiving a content data stream, comprises receiving both programs and program control information for selecting programs as said information describing a plurality of program options;

said selectively processing step comprises selecting one or more programs using a user'"'"'s programming preferences and the received program control information, wherein the user programming preferences are generated from the user specific data; and

presenting the program or information describing a program option for the selected programs to the user.

9. The method according to claim 8, wherein said user attribute comprises a semantic description of a preference.

10. The method according to claim 9, wherein said data processing step comprises determining a semantic relationship of said user preference to the information describing a plurality of program options.

11. The method according to claim 8, wherein said information describing a plurality of program options comprises a program guide.

12. The method according to claim 8, wherein said user attribute comprises a mood.

13. The method according to claim 8, wherein said user attribute comprises a demographic profile.

14. The method according to claim 8, wherein said user attribute comprises data relating to a history of use by the user.