Vocabulary engine

• US 8,661,032 B2
• Filed: 08/28/2008
• Issued: 02/25/2014
• Est. Priority Date: 08/28/2008
• Status: Active Grant

• Current Assignee: AutoData Solutions Inc.
• Original Assignee: AutoData Solutions Company (AutoData Solutions Inc.)
• Inventors: Otten, Hans, Wedermann, Christoph Alexander
• Primary Examiner(s): OBISESAN, AUGUSTINE KUNLE
• Application Number:
  US12/200,231
• Publication Number:
  US 20100057294A1
• Time in Patent Office: 2,007 Days
• Field of Search: None
• US Class Current: 707/731
• CPC Class Codes: G06Q 30/0603 Catalogue ordering

Abstract

A system and method are provided for generating an output comprising data pertaining to a vehicle. A set of vehicle data pertaining to a selected vehicle is requested and the vehicle data is obtained from a database. The vehicle data is stored, e.g. using a hash map and a script generated outside of the system is obtained, which defines the structure of the output. The script is then run while using the vehicle data to generate the output and the output is provided to an application.

Claims

1. A method for generating an output describing one or more vehicles, said method comprising:

providing a vocabulary engine for dynamically generating said output;

said vocabulary engine receiving a first request from a client interface to generate said output for said one or more vehicles;

said vocabulary engine receiving a second request from the client interface for a particular one of a plurality of predefined scripts based on client requirements specified in said second request, each of said plurality of scripts having been generated for different client requirements;

said vocabulary engine sending a third request, based on said first request, to a data source identifying one or more sets of vehicle data each specifying one or more features of a respective one of said one or more vehicles, said data source individually storing a set of vehicle data for each of a plurality of vehicles in a same format and enabling any one or more sets of vehicle data to be dynamically obtained to accommodate different outputs;

said vocabulary engine obtaining said one or more sets of vehicle data from said data source according to said third request;

said vocabulary engine storing said one or more sets of vehicle data in a memory;

said vocabulary engine generating a fourth request for said particular one of said plurality of predefined scripts based on said client requirements specified in said second request;

said vocabulary engine obtaining said particular script that is programmed to be executed by said vocabulary engine to generate said output using said one or more data sets, said script including logic defining which features from said one or more data sets are to be included in said output and how to incorporate features selected from said one or more sets of vehicle data into a textual description of one or more vehicles corresponding to said one or more sets of vehicle data;

said vocabulary engine generating said output by executing said script to determine which features to select from said one or more sets of vehicle data, and incorporating said selected features into said textual description according to said logic; and

said vocabulary engine providing said output to said client interface in response to said first and second requests.

2. The method according to claim 1, further comprising obtaining brand data to be used by said script in generating said output.

3. The method according to claim 1, further comprising specifying a set of options for at least one of said one or more vehicles, said set of options being related to said vehicle data.

4. The method according to claim 1 wherein said features are stored in said data source using a hash map.

5. The method according to claim 1 wherein said vehicle data is selected according to a vehicle code dictionary comprising a guide to comparison codes pertaining to said features, said comparison codes providing a granular breakdown of said features.

6. The method according to claim 5 wherein said comparison codes are classified according to a tree structure.

7. The method according to claim 6 wherein said tree structure comprises one or more sections, each section comprising one or more groups, each group comprising one or more families and each family comprising one or more sub-families.

8. The method according to claim 7 wherein said comparison codes comprise alphanumeric indicators for said section, said group, said family and said sub-family.

9. The method according to claim 1 wherein said vehicle data is obtained by a web server being remote from said data source.

10. The method according to claim 9 wherein said web server obtains said vehicle data from a local vehicle database, said local vehicle database obtaining one or more portions of said vehicle data from a main vehicle database, said main vehicle database having access to said data source.

11. A non-transitory computer readable medium comprising computer executable instructions for generating an output describing attributes of a one or more vehicles, said computer executable instructions comprising instructions for:

providing a vocabulary engine for dynamically generating said output;

said vocabulary engine receiving a first request from a client interface to generate said output for said one or more vehicles;

said vocabulary engine receiving a second request from the client interface for a particular one of a plurality of predefined scripts based on client requirements specified in said second request, each of said plurality of scripts having been generated for different client requirements;

said vocabulary engine sending a third request, based on said first request, to a data source identifying one or more sets of vehicle data each specifying one or more features of a respective one of said one or more vehicles, said data source individually storing a set of vehicle data for each of a plurality of vehicles in a same format and enabling any one or more sets of vehicle data to be dynamically obtained to accommodate different outputs;

said vocabulary engine obtaining said one or more sets of vehicle data from said data source according to said third request;

said vocabulary engine storing said one or more sets of vehicle data in a memory;

said vocabulary engine generating a fourth request for said particular one of said plurality of predefined scripts based on said client requirements specified in said second request;

said vocabulary engine obtaining said particular script that is programmed to be executed by said vocabulary engine to generate said output using said one or more data sets, said script including logic defining which features from said one or more data sets are to be included in said output and how to incorporate features selected from said one or more sets of vehicle data into a textual description of one or more vehicles corresponding to said one or more sets of vehicle data;

said vocabulary engine generating said output by executing said script to determine which features to select from said one or more sets of vehicle data, and incorporating said selected features into said textual description according to said logic; and

said vocabulary engine providing said output to said client interface in response to said first and second requests.

12. The computer readable medium according to claim 11, further comprising instructions for obtaining brand data to be used by said script in generating said output.

13. The computer readable medium according to claim 11, further comprising instructions for specifying a set of options for at least one of said one or more vehicles, said set of options being related to said vehicle data.

14. The computer readable medium according to claim 11 wherein said features are stored in said data source using a hash map.

15. The computer readable medium according to claim 11 wherein said vehicle data is selected according to a vehicle code dictionary comprising a guide to comparison codes pertaining to said features, said comparison codes providing a granular breakdown of said features.

16. The computer readable medium according to claim 15 wherein said comparison codes are classified according to a tree structure.

17. The computer readable medium according to claim 16 wherein said tree structure comprises one or more sections, each section comprising one or more groups, each group comprising one or more families and each family comprising one or more sub-families.

18. The computer readable medium according to claim 17 wherein said comparison codes comprise alphanumeric indicators for said section, said group, said family and said sub-family.

19. The computer readable medium according to claim 11 wherein said vehicle data is obtained by a web server being remote from said data source.

20. The computer readable medium according to claim 19 comprising instructions for said web server to obtain said vehicle data from a local vehicle database, wherein said local vehicle database obtains one or more portions of said vehicle data from a main vehicle database, said main vehicle database having access to said data source.