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Method for Efficient Documentation Updates Disclosure Number: IPCOM000198392D
Publication Date: 2010-Aug-06
Document File: 4 page(s) / 33K

Publishing Venue

The Prior Art Database


Disclosed is an invention for a recommendation engine which identifies potential sections for revision in existing product documents as a result of product changes and the release of new or updated information. The greater engine is composed of three engines that work consecutively to: split the document into logical sections, establish and assess the desired conditions for the sections, and display to the user the sections identified for revision.

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This is the abbreviated version, containing approximately 40% of the total text.

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Method for Efficient Documentation Updates

Many products have multiple long documents associated with them, especially those products with many years of development history. When products evolve through multiple releases, each release requires a product team to update associated documents. The process becomes problematic when the documents become increasingly longer with each release and the updates are amended and not replaced. Identifying where to place new or updated information becomes a challenge for developers and writers. In addition, locating updated information versus the original information is an exponentially increasing issue for customers who buy a later version of the product and upgrade throughout the evolution of the product, as well as for employees working on the project who were not on the original team.

Current attempts at addressing this issue include:

• A method which describes a background technique of highlighting search results.
[1] It does not solve the problem of updating documents.

• A method to update the metalanguage document with a delta document. [2] This method is not about judging conditions.

The disclosed invention utilizes a recommendation engine to automatically identify modules in existing product documents that need enhancements or updates due to product changes. The method improves the efficiency of the document reviewing and updating process for team members.

Common updates, and therefore targets for the recommendation engine, include:

• All versions of products and documents

• All statistical data and their time

• Limitations and restrictions

• New features

To implement this invention, developers add a function or working module to document editors or readers. This function or module needs a splitting module, a policy module and a display module.

Splitting Module Engine

The Splitting Module Engine is responsible for logically splitting a document or sections of a document into parts. An example splitting mechanism is paragraphing. In this mechanism example, a document is logically split into a few paragraphs, and each


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paragraph is a part created by the automatic splitting. This splitting module engine can be customized via certain parameters and conditions so the customer or user can add, delete and modify them. Each part becomes the creation of the Splitting Module Engine and is used by thePolicy Module Engine and the Display Module Engine.

All three modules, including the Splitting Module, start to work when the user enables the working mode. For example, the user presses a corresponding button in Graphical User Interface (GUI) mode. The Splitting Module supports three example parameters: document contents to be handled, user-defined splitting methods, and user-defined conditions.

Document contents to be handled tells which parts of the documents should be checked. One possible default value is the whole document. One example transferred value is the whole docu...