Segmenting and interpreting a document, and relocating document fragments to corresponding sections

• US 10,176,890 B2
• Filed: 06/19/2017
• Issued: 01/08/2019
• Est. Priority Date: 02/09/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Alba, Alfredo, Coden, Anni R., Drews, Clemens, Gruhl, Daniel F., Lewis, Neal R., Mendes, Pablo N., Ramakrishnan, Cartic, Terdiman, Joseph F.
• Primary Examiner(s): Paula, Cesar B
• Assistant Examiner(s): Nguyen, Luu-Phuong T
• Application Number:
  US15/627,173
• Publication Number:
  US 20180225259A1
• Time in Patent Office: 568 Days
• Field of Search: 715209
• CPC Class Codes: G06F 16/17 Details of further file system functions
• CPC Class Codes: G06F 16/3344 using natural language analysis
• CPC Class Codes: G06F 3/038 Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06F 40/103 Formatting, i.e. changing of presentation of documents automatic justification G06F40/189; automatic line break hyphenation G06F40/191
• CPC Class Codes: G06F 40/106 Display of layout of documents; Previewing
• CPC Class Codes: G06F 40/131 Fragmentation of text files, e.g. creating reusable text-blocks; Linking to fragments, e.g. using XInclude; Namespaces
• CPC Class Codes: G06F 40/166 Editing, e.g. inserting or deleting
• CPC Class Codes: G06F 40/205 Parsing
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars
• CPC Class Codes: G06F 40/237 Lexical tools
• CPC Class Codes: G06F 40/253 Grammatical analysis; Style critique
• CPC Class Codes: G06F 40/258 Heading extraction; Automatic titling; Numbering
• CPC Class Codes: G06F 40/284 Lexical analysis, e.g. tokenisation or collocates
• CPC Class Codes: G06F 40/289 Phrasal analysis, e.g. finite state techniques or chunking
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G06F 40/40 Processing or translation of natural language natural language analysis G06F40/20; semantic analysis G06F40/30
• CPC Class Codes: G10L 15/26 Speech to text systems G10L15/08 takes precedence
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 15/00 ICT specially adapted for medical reports, e.g. generation or transmission thereof

Abstract

A method comprising receiving a document having multiple sections of different types using a processor. The method also comprises obtaining a plurality of lexicons using the processor, each of the lexicons for interpreting fragments in one or more of the section types. The method further comprises interpreting fragments in a first section of the multiple sections using the processor and one or more lexicons. The method still further comprises determining, based upon the interpretation and using the processor, that a fragment in the first section is misplaced. The method still further comprises re-locating, using the processor, the misplaced fragment to a second section of the multiple sections in the document to generate a re-organized document. The method additionally includes storing the re-organized document in a hardware storage system using the processor.

Claims

1. A method, comprising:

receiving, by a processor, a document having multiple sections of different section types;

obtaining, by the processor, multiple lexicons;

interpreting, by the processor, multiple fragments in a first section of the multiple sections using one or more of the lexicons;

determining, by the processor, a section type for each fragment of the multiple fragments in the first section;

determining, by the processor, a first quantity of first fragments of the multiple fragments and a second quantity of second fragments of the multiple fragments, wherein the first fragments correspond to a first section type of the first section and the second fragments correspond to a second section type of a second section of the document;

determining, by the processor, that the first quantity of the first fragments exceeds the second quantity of the second fragments by a predetermined quantity; and

based on exceeding the predetermined quantity, re-locating the second fragments to the second section in the document or reclassifying the second fragments to correspond to the first section type.

2. The method of claim 1, wherein interpreting the fragments in the first section comprises comparing the multiple fragments to a first lexicon corresponding to the first section and comparing the multiple fragments to a second lexicon corresponding to the second section.

3. The method of claim 1, wherein interpreting the fragments in the first section comprises comparing the fragments to the multiple lexicons, each lexicon corresponding to a different one of the multiple sections.

4. The method of claim 1, further comprising converting the document from oral form to written form.

5. The method of claim 1, further comprising segmenting items in the first section into the fragments.

6. The method of claim 5, wherein the items include at least one of words, phrases, sentences, numbers, or symbols.

7. The method of claim 1, wherein interpreting the fragments comprises assigning one or more of the section types to each of the fragments using the multiple lexicons.

8. A method, comprising:

receiving a first item and a second item;

determining that the first item is a fragment matching a lexicon;

placing the fragment in a first section of a document, the first section selected based on the lexicon;

segmenting the document into multiple sections, wherein each of the multiple sections corresponds to a respective section type of multiple section types;

segmenting items in a first section of multiple sections of the document into multiple fragments, wherein the first section corresponds to a first section type;

determining a section type of each of the multiple fragments in the first section;

determining whether the multiple fragments include fragments that correspond to different section types and that are interspersed among each other approximately even proportions; and

based on the multiple fragments in the first section including fragments that correspond to different section types and that are interspersed among each other in even proportions;

determining that the fragments that correspond to different section types and that are interspersed among each other in approximately even proportions do not belong in the first section;

generating a new section corresponding to a section type that corresponds to a section type that is different than the multiple section types; and

re-locating the fragments that correspond to different section types and that are interspersed among each other in approximately even proportions to the new section.

9. The method of claim 8, wherein determining whether the multiple fragments include the fragments that correspond to the different section types and that are interspersed among each other in even proportions includes determining whether the fragments that correspond to the different section types and that are interspersed among each other in even proportions are disposed in an alternating fashion.

10. The method of claim 8, further comprising converting the document from oral form to written form.

11. The method of claim 8, wherein the items include at least one of words, phrases, sentences, numbers, or symbols.

12. A method, comprising:

receiving a document having section headers;

segmenting the document into at least first and second sections based on the section headers;

segmenting items in the first section into fragments including a first fragment and a second fragment;

identifying a section type for each of the fragments using multiple section type-specific lexicons that include a first section type-specific lexicon that corresponds to a section type of the first section and a second section type-specific lexicon that corresponds to a section type of the second section, wherein the first fragment is identified as corresponding to a different section type than the second fragment;

determining that the identified section type for at least one of the fragments corresponds to the section type of the second section;

determining a first quantity of first fragments of multiple fragments an a second quantity of second fragments of the multiple fragments, wherein the first fragments correspond to a first section type of the first section and the second fragments correspond to a second section type of a second section of the document;

determining that the first quantity of the first fragments exceeds the second quantity of the second fragments by a predetermined quantity; and

based on exceeding the predetermined quantity, relocating the at least one of the fragments to the second section based on determining that the identified section type for the at least one of the fragments corresponds to the section type of the second section.

13. The method of claim 12, wherein the document comprises an electronic health record.

14. The method of claim 12, wherein the items include non-alphabetical and non-numerical symbols.

15. The method of claim 12, wherein segmenting the items into the fragments includes identifying a portion of the items that match one of the multiple section type-specific lexicons.

16. The method of claim 12, wherein segmenting the items into the fragments includes identifying individual words in the first section that correspond to one of the multiple section type-specific lexicons.

17. The method of claim 12, wherein segmenting the items into the fragments includes identifying phrases and sentences in the first section that correspond to one of the multiple section type-specific lexicons.