System for finding a user with a preferred communication mechanism

• US 6,411,696 B1
• Filed: 12/31/1996
• Issued: 06/25/2002
• Est. Priority Date: 12/31/1996
• Status: Expired due to Fees

• Current Assignee: Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Iverson, Vaughn S., Richardson, John W.
• Primary Examiner(s): Hoosain, Allan
• Application Number:
  US08/775,507
• Time in Patent Office: 2,002 Days
• Field of Search: 379/67.1, 379/88.12, 379/88.01, 379/88.13, 379/88.18, 379/93.09, 379/201, 379/88.14, 379/210, 379/219, 379/220, 379/221, 379/70, 379/88.15, 379/88.17, 379/142.07, 379/142.14, 379/201.01, 379/201.06, 379/201.07, 379/201.11, 379/211.02, 379/212.01, 379/265.09, 379/908, 704/104, 704/243, 704/260, 709/217, 709/219, 709/203
• US Class Current: 379/201.06
• CPC Class Codes: H04M 1/65 Recording arrangements for recording a message from the calling party in the exchange H04M3/50
• CPC Class Codes: H04M 2201/40 using speech recognition speech recognition per se G10L15/00
• CPC Class Codes: H04M 2242/22 Automatic class or number identification arrangements
• CPC Class Codes: H04M 3/42042 Notifying the called party of information on the calling party details within substation equipment H04M1/57, signalling details H04Q3/72
• CPC Class Codes: H04M 3/42059 Making use of the calling party identifier
• CPC Class Codes: H04M 3/42102 Making use of the called party identifier
• CPC Class Codes: H04M 3/436 Arrangements for screening incoming calls , i.e. evaluating the characteristics of a call before deciding whether to answer it based on the calling party profile H04M3/42059; based on location H04M3/42348; based on presence H04M3/42365; diversion H04M3/54
• CPC Class Codes: Y10S 379/908 Multimedia

Abstract

A system for handling incoming media events based on content and state information. An interface which receives events transmitted via a plurality of media forwards such incoming events into an attribute extractor. The attribute extractor extracts one or more attributes from the event and passes those attributes to a characteristic accumulator. The attribute extractor may, for example, read the header of an e-mail event to determine its source or, for example, employ caller ID in conjunction with voice recognition to determine the identity of a caller.

The characteristic accumulator creates a characterization of an event on which a decision engine can base a decision of how the event should be handled. The characterization includes all extracted attributes as well as state information deemed relevant to such attributes. The decision engine will typically employ rule-based decision-making using the characterization as a starting point. The decision unit should decide both whether the event should be forwarded and along what outgoing media type. If the outgoing media type is not the same as the incoming media type, appropriate translation is provided.

Claims

1. A system comprising:

an interface for receiving events from a plurality of media;

an attribute extractor coupled to the interface for extracting an attribute from an event received across one of the media wherein the attribute extractor comprises a parser;

a characteristic accumulator coupled to the attribute extractor which accumulates relevant attributes and state information relating to the event; and

a decision engine coupled to the characteristic accumulator which determines, based on the attributes and state information, how the event should be handled, the decision engine having adaptive learning capability.

2. The system of claim 1 further comprising:

a translation unit for translating between a first media type of an incoming event to a second media type of an outgoing event.

3. The system of claim 2 wherein the translation unit comprises:

a media specific array to map the first media type to the second media type; and

a media specific filter to render a portion of the incoming event relevant to the second media type when the first and second media types are not the same.

4. The system of claim 3 wherein the media specific array and the media specific filter are modified responsive to rules and state information associated with the system.

5. The system of claim 3 wherein the decision engine selects the second media type.

6. The system of claim 2 wherein the translation unit generates a notification event compatible with the second media type responsive to the incoming event being forwarded to the translation unit by the decision unit.

7. The system of claim 2 wherein the translation unit comprises:

an optical character recognition unit;

a text to speech unit;

a speech to text unit; and

a graphic to fax unit.

8. The system of claim 1 wherein the attribute extractor, the characteristic accumulator, and decision engine are implemented as a single microprocessor.

9. The system of claim 1 wherein the decision engine includes at least one of an expert system, a rule-based learning system, and a neural net.

10. The system of claim 1 wherein the attribute extractor further comprises:

a voice recognition unit; and

a speech recognition unit.

11. The system of claim 1 wherein the adaptive learning capability is based on implicit input.

12. A method of establishing communication between a remote party and a user comprising:

identifying using a parser an attribute of an event received via one of a plurality of media;

grouping the attribute with current state information; and

determining using adaptive learning, based on the attribute and state information, a best medium to contact the user.

13. The method of claim 12 further comprising:

translating at least a portion of the event from an incoming media type to an outgoing media type.

14. The method of claim 12 wherein determining is performed using a subset of:

a plurality of pre-recorded rules, a plurality of user-entered rules, and a plurality of computer-generated rules.

15. The method of claim 12 further comprising:

retaining as state information a context in which the event was handled.

16. The method of claim 12 further comprising:

iteratively sending notification events to media types in a hierarchical order until contact is established or all supported media types are exhausted.

17. A system comprising:

an interface for receiving events from a plurality of media;

an attribute extractor coupled to the interface for extracting an attribute from an event received across one of the media, wherein the attribute extractor comprises a stress analyzer;

a characteristic accumulator coupled to the attribute extractor which accumulates relevant attributes and state information relating to the event; and

a decision engine coupled to the characteristic accumulator which determines, based on the attributes and state information, how the event should be handled, the decision engine having adaptive learning capability.

18. The system of claim 17 wherein the adaptive learning capability is based on implicit input.