Method and apparatus for template-based processing of electronic documents

• US 8,521,757 B1
• Filed: 09/26/2008
• Issued: 08/27/2013
• Est. Priority Date: 09/26/2008
• Status: Active Grant

• Current Assignee: Veritas Technologies, LLC (Whitehouse Group Ltd.)
• Original Assignee: Symantec Corporation (NortonLifeLock Inc.)
• Inventors: Nanda, Bijaya Laxmi, Kabra, Navin, Rajan, Basant
• Primary Examiner(s): Ruiz, Angelica
• Application Number:
  US12/239,175
• Time in Patent Office: 1,796 Days
• Field of Search: None
• US Class Current: 707/758
• CPC Class Codes: G06F 16/93 Document management systems
• CPC Class Codes: G06F 40/10 Text processing natural language analysis G06F40/20; semantic analysis G06F40/30; processing or translation of natural language G06F40/40
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

Method and apparatus for template-based processing of electronic documents is described. In some examples, text content of the electronic documents is analyzed to identify whether each of the electronic documents matches any of a plurality of document templates. A template index is generated that relates at least one of the electronic documents with at least one of the plurality of document templates associated therewith. A search query is generated using at least one of the plurality of document templates as a respective at least one search parameter. An archive having the electronic documents is searched using the template index to locate any of the electronic documents that match the at least one document template of the search query.

Claims

1. A computer implemented method of processing electronic documents, comprising:

analyzing text content of the electronic documents to identify whether each of the electronic documents matches any of a plurality of predefined document templates, wherein one or more of the electronic documents conforms to a structure of at least one of the plurality of predefined document templates, and wherein the step of analyzing comprises executing at least one machine learning algorithm, the at least one machine learning algorithm trained using at least one sample electronic document having a predefined template;

generating a template index that relates at least one of the electronic documents with at least one of the plurality of predefined document templates based at least in part upon an identified match between the at least one of the electronic documents and the at least one of the plurality of predefined document templates;

generating a search query using at least one of the plurality of predefined document templates as at least one search parameter;

searching an archive having the electronic documents using the template index to locate one or more of the electronic documents that match the at least one predefined document template of the search query; and

providing access to the one or more of the electronic documents that match the at least one predefined document template of the search query.

2. The method of claim 1, wherein the at least one machine learning algorithm is responsive to text constructs in the text content of the electronic documents to identify whether each of the electronic documents matches any of the plurality of predefined document templates.

3. The method of claim 2, further comprising:

detecting, through the execution of the at least one machine learning algorithm, at least one new document template; and

adding the at least one new document template to the plurality of predefined document templates.

4. The method of claim 1, further comprising:

generating a list including at least one of the electronic documents that does not match any of the plurality of predefined document templates.

5. The method of claim 1, further comprising:

generating at least one new document template based on one or more predefined rules.

6. The method of claim 1, further comprising:

analyzing a predefined native document template of at least one of the electronic documents to identify whether the predefined native template thereof matches any of a plurality of predefined document templates.

7. An apparatus for processing electronic documents, comprising:

means for analyzing text content of the electronic documents to identify whether each of the electronic documents matches any of a plurality of predefined document templates, wherein one or more of the electronic documents conforms to a structure of at least one of the plurality of predefined document templates, and wherein the means for analyzing comprises means for executing at least one machine learning algorithm, the at least one machine learning algorithm trained using at least one sample electronic document having a predefined template;

means for generating a template index that relates at least one of the electronic documents with at least one of the plurality of predefined document templates based at least in part upon an identified match between the at least one of the electronic documents and the at least one of the plurality of predefined document templates;

means for generating a search query using at least one of the plurality of predefined document templates as at least one search parameter;

means for searching an archive having the electronic documents using the template index to locate one or more of the electronic documents that match the at least one predefined document template of the search query; and

means for providing access to the one or more of the electronic documents that match the at least one predefined document template of the search query.

8. The apparatus of claim 7, wherein the at least one machine learning algorithm is responsive to text constructs in the text content of the electronic documents to identify whether each of the electronic documents matches any of the plurality of predefined document templates.

9. The apparatus of claim 7, further comprising:

means for generating at least one of the plurality of document templates based on one or more predefined rules.