Authors:
Julia Patten
Abstract:
This disclosure proposes a solution that adds keywords to configurations that can be used with an ETL (Extract, Transform, Load) strategy to create a tree structure of options and their values. This structure can be sequentially traversed to create text thereby documenting the actual configuration values in use.
Background:
The problem being solved is to document all the active configurations and their values in a system. If there are many configuration values, it's hard to know what the whole setup of the system is without having to review each value and document it manually to create an entire picture. An automated output of all the configuration and values is useful to provide the vendor for problem determination, and for a customer to review to get an overview of all of the current business rule settings. Frequently software customers or internal software testers do not know what the sum of their system configuration is. Each value can be looked up but this takes time and, unless written down, doesn't create a complete picture of the system configurations and rules.
Description:
By adding a keyword to each configuration setting, extracting all of the configurations, and transforming them into tokens in a grouped structure, the structure can be traversed to create a rough text representation of the configurations.
For example:
Tag the configuration
COUPON_LIMIT_AMOUNT can have a tag of “COUPON”
MULTIPLY_COUPONS_DAYS can also have a tag of “COUPON”
Extract all of the configuration data
Transform
- Create tokens such as ‘COUPON’ ‘Limit’ ‘Amount’ including the tag value as the first in the structure
- Combine like values into a tree structure as much as possible
- ‘coupon’-> ‘limit’ -> ‘amount’
- ‘coupon’-> ‘limit’ -> ‘quantity’
Traverse the tree structure to document the system configuration.
Coupon limit amount is $5.00
Coupon limit total transaction amount is $20.00
Coupon limit total transaction quantity is 15
Supporting Art:
https://patents.google.com/patent/CN1984133B/en - Method for forming structured tree
Abstract
This invention discloses a method of forming the structure tree. The method includes: save the structure tree's xml configuration file to the server; the client downloads xml configuration file from the server; the client reads structure tree's attribute that is contained in xml configuration file, according to attribute it forms structure tree step by step. Using the method of this invention, it can simply and intuitional form information structure tree with the abundant structure and intricate meaning. It avoids client and the server's private agreement. It needn't exploit the single server processes, and it needn't customers perform complex interactive logic to perform structure tree information. It has augment ability.
https://patents.google.com/patent/US20100043012
Electronic device system and sharing method thereof
Abstract
An electronic system comprises a memory, a parser, and a device driver. A plurality of applications and a document are stored in a user space of the memory, the document storing configuration parameters. The parser module parses the document to retrieve the parameters in response to invocation from at least one application. The device driver creates data structure for the parameters in the kernel space of the memory, thus to facilitate a plurality of programs to execute different functions of the system by commonly utilizing the parameters through the device driver.
https://patents.google.com/patent/US7937263
System and method for tokenization of text using classifier models
Abstract
The present invention pertains to a system and method for the tokenization of text. The featurizer may be configured to receive input text and convert the input text into tokens. According to one aspect of the invention, the tokens may include only one type of character, the characters selected from the group consisting of letters, numbers, and punctuation. The tokenizer may also include a classifier. The classifier may be configured to receive the tokens from the featurizer. Furthermore, the classifier may be configured to analyze the tokens received from the featurizer to determine if the tokens may be input into a predetermined classification model using a preclassifier. If one of the tokens passes the preclassifier, then the token is classified using the predetermined classification model. Additionally, according to a first aspect of the invention, the tokenizer may also include a finalizer. The finalizer may be configured to receive the tokens and may be configured to produce a final output.
TGCS Reference 2892
