Creation of component templates based on semantically similar content

Patent metadata

Field	Value
Publication number	US-12197873-B2
Application number	US-202318544159-A
Country	US
Kind code	B2
Filing date	Dec 18, 2023
Priority date	Feb 14, 2020
Publication date	Jan 14, 2025
Grant date	Jan 14, 2025

Abstract

Systems, methods and products for accessing a set of electronic document templates, identifying instances of common document content such as content items which are semantically similar, and generating component templates containing the common content. Semantically similar content may be identified by analyzing content for factors such as expressed sentiment, included keyphrases, recognizable entities, expressed topics, assigning values to content based on these factors, and determining similarity based on comparisons of the assigned values. Component templates may also be generated based on types of content that include identical text or images, content that has a predefined level of similarity rather than being identical, content that has common rules, scripting logic or variables, metadata, etc. The component templates may be generated automatically, or in response to user instructions.

First claim

What is claimed is:

1. A system comprising:
one or more computer processors and one or more computer memories, the one or more computer processors adapted to:
determine, for each of a plurality of content instances in a set of electronic documents, one or more corresponding values for corresponding semantic factors;
store, for each of the plurality of content instances, the corresponding values for the corresponding semantic factors in a data structure associated with the content item;
for one or more pairs of the plurality of content instances:
compare respective values of the corresponding data structures to determine similarity scores for each of the semantic factors;
weight and combine the similarity scores for the semantic factors to determine a degree of similarity of the pair of the plurality of content instances;
compare the corresponding degree of similarity to a threshold value to determine whether the pair of the plurality of content instances is semantically similar.

2. The system of claim 1 , wherein the one or more computer processors are configured to create a component template corresponding to two or more electronic document templates of a set of electronic document templates, wherein the component template contains one or more content instances in the two or more electronic document templates that are determined to be semantically similar, and store the component template in the one or more computer memories.

3. The system of claim 1 , wherein the one or more computer processors are configured to, for each of the content instances, store the values for each of the one or more semantic factors in a corresponding vector.

4. The system of claim 3 , wherein the degree of similarity between the content instances is determined by comparing the respective semantic factor values of the vectors corresponding to the content instances, determining the degree of similarity of the content instances with respect to each semantic factor, and summing the degrees of similarity of the content instances for all of the semantic factors to generate a similarity score.

5. The system of claim 1 , wherein the one or more computer processors are adapted to, for each electronic document template of a set of electronic document templates:
analyze content therein and thereby
determine a sentiment associated with the electronic document template,
recognize entities identified in the electronic document template,
identify keyphrases contained in the electronic document template, and
identify topics contained in the electronic document template; and

identify semantically similar content instances by comparing the identified sentiments, the recognized entities, the identified keyphrases, and the identified topics in each electronic document template of the set of electronic document templates.

6. The system of claim 5 , wherein identifying the semantically similar content instances comprises computing a semantic distance between two electronic document templates of the set of electronic document templates, wherein the semantic distance is determined based on one or more of:
a first similarity value representative of a similarity between sentiments associated with the two electronic document templates of the set of electronic document templates,
a second similarity value representative of recognized entities identified in the two electronic document templates of the set of electronic document templates,
a third similarity value representative of a similarity between identified keyphrases contained in the two electronic document templates of the set of electronic document templates, and
a fourth similarity value representative of a similarity between identified topics contained in the two electronic document templates of the set of electronic document templates.

7. A computer program product comprising a non-transitory computer-readable medium storing instructions executable by one or more processors to perform:
determining, for each of a plurality of content instances in a set of electronic documents, one or more corresponding values for corresponding semantic factors;
storing, for each of the plurality of content instances, the corresponding values for the corresponding semantic factors in a data structure associated with the content item;
for one or more pairs of the plurality of content instances:
comparing respective values of the corresponding data structures to determine similarity scores for each of the semantic factors;
weighting and combining the similarity scores for the semantic factors to determine a degree of similarity of the pair of the plurality of content instances;
comparing the corresponding degree of similarity to a threshold value to determine whether the pair of the plurality of content instances is semantically similar.

8. The computer program product of claim 7 , wherein the instructions are further executable by the one or more processors to create a component template corresponding to two or more electronic document templates of a set of electronic document templates, wherein the component template contains one or more content instances in the two or more electronic document templates that are determined to be semantically similar, and store the component template.

9. The computer program product of claim 7 , wherein the instructions are further executable by the one or more processors to analyze, for each electronic document template of a set of electronic document templates, content therein and determine a sentiment associated with the electronic document template, the instructions being further executable by the one or more processors to identify semantically similar content instances by comparing at least the sentiment associated with each electronic document template of the set of electronic document templates.

10. The computer program product of claim 7 , wherein the instructions are further executable by the one or more processors to analyze, for each electronic document template of a set of electronic document templates, content therein and recognize entities identified therein, the instructions being further executable by the one or more processors to identify semantically similar content instances by comparing at least the recognized entities identified in each electronic document template of the set of electronic document templates.

11. The computer program product of claim 7 , wherein the instructions are further executable by the one or more processors to analyze, for each electronic document template of a set of electronic document templates, content therein and identify keyphrases contained therein, the instructions being further executable by the one or more processors to identify semantically similar content instances by comparing at least the identified keyphrases in each electronic document template of the set of electronic document templates.

12. The computer program product of claim 7 , wherein the instructions are further executable by the one or more processors to analyze, for each electronic document template of a set of electronic document templates, content therein and identify topics contained therein, the instructions being further executable by the one or more processors to identify semantically similar content instances by comparing at least the identified topics in each electronic document template of the set of electronic document templates.

13. The computer program product of claim 7 , wherein the instructions are further executable by the one or more processors to, for each electronic document template of a set of electronic document templates,
analyze content therein and thereby
determine

Assignees

• Open Text Holdings Inc

Inventors

• Downs James Matthew
• Wiley Anthony

Classifications

• G06F40/289

  Phrasal analysis, e.g. finite state techniques or chunking · CPC title

• G06F40/186

  Templates · CPC title

• G06F40/30 Primary

  Semantic analysis · CPC title